Fig 5 Variants and fusions

Variants

ALS vs CTRL variant number

answerals.vcfannotate.samples_no_variants = answerals.metadata$dataset_sample[!answerals.metadata$dataset_sample %in% answerals.vcfannotate$dataset_sample] # 0 i.e. all samples have at least 1 variant
answerals.vcfannotate.totals = answerals.vcfannotate %>% distinct(dataset_sample, .keep_all = TRUE) #keep 1 row per sample for total number of variants

# generalised linear model spline
answerals.vcfannotate.totals.glm = glm(data=answerals.vcfannotate.totals, total ~ CONDITION + rms::rcs(total_reads, 3), family = poisson)
summary(answerals.vcfannotate.totals.glm)
## 
## Call:
## glm(formula = total ~ CONDITION + rms::rcs(total_reads, 3), family = poisson, 
##     data = answerals.vcfannotate.totals)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -20.100   -6.822   -2.358    2.699   48.785  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           1.063e+01  3.409e-03 3119.19   <2e-16 ***
## CONDITIONALS                          1.020e-02  7.027e-04   14.52   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads   4.116e-09  4.353e-11   94.54   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads' -2.174e-09  5.152e-11  -42.20   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 54707  on 279  degrees of freedom
## Residual deviance: 36003  on 276  degrees of freedom
## AIC: 39600
## 
## Number of Fisher Scoring iterations: 3
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           1.063e+01  3.409e-03 3119.19   <2e-16 ***
# CONDITIONALS                          1.020e-02  7.027e-04   14.52   <2e-16 ***

# Violin total variant events
answerals.vcfannotate.totals.stats = tibble(group1 = "CTRL", group2 = "ALS", p.signif = "****", y.position = 75000, xmin = 1, xmax = 2)
answerals.vcfannotate.total.violin <- violin_plot(answerals.vcfannotate.totals, color_by = "CONDITION", continuous = "total", cols = c("dodgerblue2", "firebrick2"), one_sample = FALSE, plot_stats = FALSE, arrow_labels = FALSE, ylims = c(50000,76000), dpi = 72, ylabel = "Total Number of Variants", title = "All Variant types") +
  stat_pvalue_manual(answerals.vcfannotate.totals.stats, tip.length = 0.01, size = 4)
answerals.vcfannotate.total.violin

Variant types

SNP

answerals.vcfannotate.snp = answerals.vcfannotate %>% filter(variant_type == "SNP") 
# add samples with 0 variants for each variant type
samples_no_SNP = answerals.metadata$dataset_sample[!answerals.metadata$dataset_sample %in% pull(answerals.vcfannotate.snp,dataset_sample)] 
answerals.vcfannotate.snp.glm = glm(data = answerals.vcfannotate.snp, n ~ CONDITION + rms::rcs(total_reads, 3), family = poisson)
summary(answerals.vcfannotate.snp.glm)
## 
## Call:
## glm(formula = n ~ CONDITION + rms::rcs(total_reads, 3), family = poisson, 
##     data = answerals.vcfannotate.snp)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -18.267   -6.464   -2.250    2.197   46.466  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           1.048e+01  3.680e-03 2847.29   <2e-16 ***
## CONDITIONALS                          8.880e-03  7.581e-04   11.71   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads   4.164e-09  4.700e-11   88.61   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads' -2.299e-09  5.564e-11  -41.33   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 48499  on 279  degrees of freedom
## Residual deviance: 32867  on 276  degrees of freedom
## AIC: 36421
## 
## Number of Fisher Scoring iterations: 3
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           1.048e+01  3.680e-03 2847.29   <2e-16 ***
# CONDITIONALS                          8.880e-03  7.581e-04   11.71   <2e-16 ***
answerals.vcfannotate.snp.stats = tibble(group1 = "CTRL", group2 = "ALS", p.signif = "****", y.position = 62000, xmin = 1, xmax = 2)
answerals.vcfannotate.snp.violin <- violin_plot(answerals.vcfannotate.snp, color_by = "CONDITION", continuous = "n", cols = c("dodgerblue2", "firebrick2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(40000,64000), dpi = 72, ylabel = "Number of Variants", title = "SNV")  +
  stat_pvalue_manual(answerals.vcfannotate.snp.stats, tip.length = 0.01, size = 4)
answerals.vcfannotate.snp.violin

Insertions

answerals.vcfannotate.insertion = answerals.vcfannotate %>% filter(variant_type == "Insertion") 
# add samples with 0 variants for each variant type
samples_no_Insertion = answerals.metadata$dataset_sample[!answerals.metadata$dataset_sample %in% pull(answerals.vcfannotate.insertion,dataset_sample)]
answerals.vcfannotate.Insertion.glm = glm(data = answerals.vcfannotate.insertion, n ~ CONDITION + rms::rcs(total_reads, 3), family = poisson)
summary(answerals.vcfannotate.Insertion.glm)
## 
## Call:
## glm(formula = n ~ CONDITION + rms::rcs(total_reads, 3), family = poisson, 
##     data = answerals.vcfannotate.insertion)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -15.4957   -2.8982   -0.3836    3.0568   20.8196  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           8.121e+00  1.219e-02 666.031  < 2e-16 ***
## CONDITIONALS                          1.928e-02  2.528e-03   7.624 2.47e-14 ***
## rms::rcs(total_reads, 3)total_reads   3.391e-09  1.557e-10  21.781  < 2e-16 ***
## rms::rcs(total_reads, 3)total_reads' -6.114e-10  1.837e-10  -3.329 0.000873 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 9242.2  on 279  degrees of freedom
## Residual deviance: 7330.3  on 276  degrees of freedom
## AIC: 10212
## 
## Number of Fisher Scoring iterations: 3
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           8.121e+00  1.219e-02 666.031  < 2e-16 ***
# CONDITIONALS                          1.928e-02  2.528e-03   7.624 2.47e-14 ***

answerals.vcfannotate.insertion.stats = tibble(group1 = "CTRL", group2 = "ALS", p.signif = "****", y.position = 6400, xmin = 1, xmax = 2)
answerals.vcfannotate.insertion.violin <- violin_plot(answerals.vcfannotate.insertion, color_by = "CONDITION", continuous = "n", cols = c("dodgerblue2", "firebrick2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(3500,6700), dpi = 72, ylabel = "", title = "Insertion")  +
  stat_pvalue_manual(answerals.vcfannotate.insertion.stats, tip.length = 0.01, size = 4)
answerals.vcfannotate.insertion.violin

Deletions

answerals.vcfannotate.deletion = answerals.vcfannotate %>% filter(variant_type == "Deletion") 
samples_no_Deletion = answerals.metadata$dataset_sample[!answerals.metadata$dataset_sample %in% pull(answerals.vcfannotate.deletion,dataset_sample)] 
answerals.vcfannotate.Deletion.glm = glm(data = answerals.vcfannotate.deletion, n ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
summary(answerals.vcfannotate.Deletion.glm)
## 
## Call:
## glm(formula = n ~ CONDITION + rms::rcs(total_reads, 3), family = poisson, 
##     data = answerals.vcfannotate.deletion)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -6.5241  -1.4909  -0.2659   0.8584   9.7615  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           7.858e+00  1.351e-02  581.45  < 2e-16 ***
## CONDITIONALS                          1.701e-02  2.789e-03    6.10 1.06e-09 ***
## rms::rcs(total_reads, 3)total_reads   4.337e-09  1.726e-10   25.13  < 2e-16 ***
## rms::rcs(total_reads, 3)total_reads' -2.406e-09  2.041e-10  -11.79  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 3408.5  on 279  degrees of freedom
## Residual deviance: 2102.7  on 276  degrees of freedom
## AIC: 4929
## 
## Number of Fisher Scoring iterations: 3
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           7.858e+00  1.351e-02  581.45  < 2e-16 ***
# CONDITIONALS                          1.701e-02  2.789e-03    6.10 1.06e-09 ***
answerals.vcfannotate.insertion.stats = tibble(group1 = "CTRL", group2 = "ALS", p.signif = "****", y.position = 4900, xmin = 1, xmax = 2)
answerals.vcfannotate.deletion.violin <- violin_plot(answerals.vcfannotate.deletion, color_by = "CONDITION", continuous = "n", cols = c("dodgerblue2", "firebrick2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(3000,5000), dpi = 72, ylabel = "", title = "Deletion") +
  stat_pvalue_manual(answerals.vcfannotate.insertion.stats, tip.length = 0.01, size = 4)
answerals.vcfannotate.deletion.violin

Substitutions

library(MutationalPatterns)
ref_genome <- "BSgenome.Hsapiens.UCSC.hg38"
library(ref_genome, character.only = TRUE)
type_occurrences = readRDS(here(shared_path, "answerals/rnavar/mutationalpatterns/type_occurrences.RDS"))
answerals.multiqc_rseqc_read_distribution.tsv = read_tsv(here(shared_path,"answerals/nfcore/multiqc/star_salmon/multiqc_data/multiqc_rseqc_read_distribution.txt"), show_col_types = FALSE) %>% clean_names()
answerals.base_substitutions = type_occurrences %>% as_tibble(rownames = "sample") %>% select(-`C>T at CpG`, -`C>T other`) %>%
  left_join(select(answerals.metadata, sample, condition)) %>% 
  pivot_longer(!c(condition, sample), names_to = "Substitution", values_to = "count") %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), Substitution = as.factor(Substitution)) %>%
  left_join(select(answerals.multiqc_rseqc_read_distribution.tsv, sample, total_reads))

# ### C>A
# glm_starfusion_C_A = glm(data = filter(answerals.base_substitutions, Substitution == "C>A"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_C_A)
# # Coefficients:
# #                                        Estimate Std. Error z value Pr(>|z|)    
# # (Intercept)                           7.672e+00  1.443e-02 531.861  < 2e-16 ***
# # CONDITIONALS                          8.564e-03  2.952e-03   2.901  0.00372 ** 
# 
# ### C>G
# glm_starfusion_C_G = glm(data = filter(answerals.base_substitutions, Substitution == "C>G"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_C_G)
# # Coefficients:
# #                                        Estimate Std. Error z value Pr(>|z|)    
# # (Intercept)                           8.085e+00  1.230e-02 657.069   <2e-16 ***
# # CONDITIONALS                          3.246e-03  2.533e-03   1.281      0.2    
# 
# ### C>T
# glm_starfusion_C_T = glm(data = filter(answerals.base_substitutions, Substitution == "C>T"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_C_T)
# # Coefficients:
# #                                        Estimate Std. Error  z value Pr(>|z|)    
# # (Intercept)                           9.365e+00  6.467e-03 1448.230  < 2e-16 ***
# # CONDITIONALS                          4.251e-03  1.331e-03    3.193  0.00141 ** 
# 
# ### T>A
# glm_starfusion_T_A = glm(data = filter(answerals.base_substitutions, Substitution == "T>A"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_T_A)
# # Coefficients:
# #                                        Estimate Std. Error z value Pr(>|z|)    
# # (Intercept)                           7.247e+00  1.803e-02 401.926  < 2e-16 ***
# # CONDITIONALS                          1.202e-02  3.700e-03   3.247  0.00117 ** 
# 
# ### T>C
# glm_starfusion_T_C = glm(data = filter(answerals.base_substitutions, Substitution == "T>C"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_T_C)
# # Coefficients:
# #                                        Estimate Std. Error z value Pr(>|z|)    
# # (Intercept)                           9.563e+00  5.869e-03 1629.54   <2e-16 ***
# # CONDITIONALS                          1.433e-02  1.214e-03   11.81   <2e-16 ***
# 
# ### T>G
# glm_starfusion_T_G = glm(data = filter(answerals.base_substitutions, Substitution == "T>G"), count ~ CONDITION + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion_T_G)
# # Coefficients:
# #                                        Estimate Std. Error z value Pr(>|z|)    
# # (Intercept)                           7.741e+00  1.456e-02 531.774   <2e-16 ***
# # CONDITIONALS                          2.634e-03  2.995e-03   0.879    0.379    


ipsc_mn_als_datasets.Substitution.stat <- answerals.base_substitutions %>% group_by(Substitution) %>% t_test(count ~ CONDITION) %>% mutate(p.signif = c("**","ns","**","**","****","ns"), y.position = c(4500,5500,20500,2700,25000,3900)) 
# ipsc_mn_als_datasets.Substitution.stat
# # Substitution .y.   group1 group2    n1    n2 statistic    df      p p.signif y.position
# #   <fct>        <chr> <chr>  <chr>  <int> <int>     <dbl> <dbl>  <dbl> <chr>         <dbl>
# # 1 C>A          count CTRL   ALS       42   238     -2.14  59.5 0.0362 **             4500
# # 2 C>G          count CTRL   ALS       42   238     -1.77  62.4 0.0812 ns             5500
# # 3 C>T          count CTRL   ALS       42   238     -1.86  63.6 0.0672 **            20500
# # 4 T>A          count CTRL   ALS       42   238     -2.27  56.2 0.0269 **             2700
# # 5 T>C          count CTRL   ALS       42   238     -2.23  56.0 0.0294 ****          25000
# # 6 T>G          count CTRL   ALS       42   238     -1.86  63.8 0.0674 ns             3900
answerals.base_substitutions.violin <- ggplot(answerals.base_substitutions, aes(x = CONDITION, y = count, colour = CONDITION)) +
    ggrastr::rasterise(geom_violin(adjust = 1), dpi = 72) +
    ggrastr::rasterise(geom_sina(size = 0.5), dpi = 72) +
    ggrastr::rasterise(geom_boxplot(aes(fill = CONDITION), colour = "black", width=0.2, alpha = 0.5, outlier.shape = NA), dpi = 72) + 
    scale_colour_manual(values = c("dodgerblue2", "firebrick2")) + scale_fill_manual(values = c("dodgerblue2", "firebrick2")) +
    theme_oz() + theme(legend.position = "none", plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5), panel.border = element_blank(), axis.ticks = element_line(colour = "black") ) +
    facet_wrap(~ Substitution, scales = "free", nrow = 2)  + labs(y = "Number of Variants", x = "") + #, title = "Base substitution types"
    stat_pvalue_manual(ipsc_mn_als_datasets.Substitution.stat, label = "p.signif", tip.length = 0.01, size = 4, hide.ns = TRUE)
answerals.base_substitutions.violin

Fusions

Venn overlap unqiue gene fusions

ipsc_mn_als_datasets.starfusion.als_events <- ipsc_mn_als_datasets.starfusion %>% filter(condition == "als") %>% distinct(fusion_name) %>% pull(fusion_name)
ipsc_mn_als_datasets.starfusion.ctrl_events <- ipsc_mn_als_datasets.starfusion %>% filter(condition == "ctrl") %>% distinct(fusion_name) %>% pull(fusion_name)
ipsc_mn_als_datasets.starfusion.als_ctrl_events <- list("ALS" = ipsc_mn_als_datasets.starfusion.als_events, "CTRL" = ipsc_mn_als_datasets.starfusion.ctrl_events)
ipsc_mn_als_datasets.starfusion.als_ctrl_events_venn <- ggvenn(ipsc_mn_als_datasets.starfusion.als_ctrl_events, fill_color = c("firebrick2", "dodgerblue2"), set_name_color = c("firebrick2", "dodgerblue2"), show_percentage = FALSE, stroke_size = 0.4, set_name_size = 3.5) + labs(subtitle = "Unique Gene Fusions")  + 
  theme(plot.subtitle = element_text(hjust = 0.5, size = 9), plot.margin = unit(c(0, -1, 0, -1), "lines"))
ipsc_mn_als_datasets.starfusion.als_ctrl_events_venn

Violin ALS vs CTRL

ipsc_mn_als_datasets.starfusion.n = ipsc_mn_als_datasets.starfusion %>% 
  add_count(dataset_sample) %>% # count number of fusions per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, dataset, total_reads) #keep 1 row per sample

# add samples with 0 fusions
ipsc_mn_als_datasets.starfusion.samples_no_fusions = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% ipsc_mn_als_datasets.starfusion.n$dataset_sample] # "smith_tardbp_1" "smith_ctrl_1"  0 events
ipsc_mn_als_datasets.paired_end.metadata.no_fusions = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% ipsc_mn_als_datasets.starfusion.samples_no_fusions) %>% 
  left_join(multiqc_rseqc_read_distribution.tsv) %>%
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), n = 0) %>% select(dataset_sample, n, CONDITION, dataset, total_reads)
ipsc_mn_als_datasets.starfusion.n = bind_rows(ipsc_mn_als_datasets.starfusion.n, ipsc_mn_als_datasets.paired_end.metadata.no_fusions)

glm_starfusion = glm(data = ipsc_mn_als_datasets.starfusion.n, n ~ CONDITION + dataset + rms::rcs(total_reads, 3), family=poisson)
summary(glm_starfusion)
## 
## Call:
## glm(formula = n ~ CONDITION + dataset + rms::rcs(total_reads, 
##     3), family = poisson, data = ipsc_mn_als_datasets.starfusion.n)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -3.7724  -1.0338  -0.2193   0.6234   5.8605  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           2.121e+00  3.330e-01   6.369 1.90e-10 ***
## CONDITIONALS                          1.327e-01  4.282e-02   3.098  0.00195 ** 
## datasetcatanese                      -2.166e-01  1.355e-01  -1.599  0.10981    
## datasetdafinca.c9orf72               -1.340e+00  2.147e-01  -6.243 4.30e-10 ***
## datasetdafinca.tardbp                -4.989e-01  2.798e-01  -1.783  0.07455 .  
## datasetdesantis                      -5.775e-01  2.751e-01  -2.099  0.03584 *  
## datasetkiskinis                       7.013e-01  2.969e-01   2.362  0.01816 *  
## datasetneurolincs.diMN               -4.582e-01  6.999e-02  -6.546 5.90e-11 ***
## datasetneurolincs.iMN                -8.916e-01  1.271e-01  -7.016 2.28e-12 ***
## datasetsmith                         -2.752e+00  6.484e-01  -4.244 2.20e-05 ***
## datasetsommer                        -1.106e+00  1.971e-01  -5.614 1.98e-08 ***
## datasetwang                           3.354e-01  2.454e-01   1.367  0.17173    
## rms::rcs(total_reads, 3)total_reads   5.115e-09  4.914e-09   1.041  0.29785    
## rms::rcs(total_reads, 3)total_reads' -7.908e-09  3.231e-09  -2.447  0.01439 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 1202.77  on 395  degrees of freedom
## Residual deviance:  747.06  on 382  degrees of freedom
## AIC: 2356.8
## 
## Number of Fisher Scoring iterations: 4
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           2.121e+00  3.330e-01   6.369 1.90e-10 ***
# CONDITIONALS                          1.327e-01  4.282e-02   3.098  0.00195 ** 

ipsc_mn_als_datasets.starfusion.n.stats = tibble(group1 = "CTRL", group2 = "ALS", p.signif = "**", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.n, color_by = "CONDITION", continuous = "n", cols = c("dodgerblue2", "firebrick2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,42), dpi = 72, ylabel = "Number of Fusion Events", title = "All Fusion types") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.n.stats, tip.length = 0.01, size = 4)
ipsc_mn_als_datasets.starfusion.violin

Table S8 Variants per sample

answerals.vcfannotate.s8 = answerals.vcfannotate %>% select(dataset, sample, n, variant_type, condition, mutation, Total = total) %>% 
  pivot_wider(names_from = "variant_type", values_from = "n", values_fill = 0) %>% 
  select(dataset, sample, condition, mutation, Total, SNP, Insertion, Deletion) %>% #, Complex
  arrange(condition)
kbl(answerals.vcfannotate.s8) %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), fixed_thead = T) %>% scroll_box(width = "100%", height = "500px")
dataset sample condition mutation Total SNP Insertion Deletion
answerals CASE_NEUDE902GCT als c9orf72 56617 48220 4710 3675
answerals CASE_NEUAA599TMX als sporadic 56584 48981 3870 3725
answerals CASE_NEUAB000NKC als c9orf72 56355 48388 4636 3326
answerals CASE_NEUAE228FF6 als sporadic 56503 48530 4342 3623
answerals CASE_NEUAE993EPR als sporadic 70176 60471 5233 4453
answerals CASE_NEUAF553MJ3 als sporadic 57107 49228 4267 3603
answerals CASE_NEUAG241NUD als sporadic 57675 49382 4400 3885
answerals CASE_NEUAG603XLK als pfn1 47174 40535 3639 2994
answerals CASE_NEUAG766ULB als sporadic 60427 51744 4934 3742
answerals CASE_NEUAL076FCE als sporadic 59793 50869 4989 3924
answerals CASE_NEUAM655HF7 als sporadic 55081 47208 4230 3634
answerals CASE_NEUAP285GGU als sporadic 56688 48716 4429 3537
answerals CASE_NEUAT234RK6 als sporadic 57608 49123 4986 3488
answerals CASE_NEUAW157NMJ als sporadic 58189 50092 4436 3653
answerals CASE_NEUAW717TN6 als sporadic 57854 49562 4370 3910
answerals CASE_NEUAX665ZHY als sporadic 57161 48894 4469 3789
answerals CASE_NEUAY067UTB als chchd1 60322 51828 4567 3919
answerals CASE_NEUAZ394JEZ als sporadic 62141 53706 4534 3890
answerals CASE_NEUBA169GXD als sporadic 60349 51652 4797 3890
answerals CASE_NEUBC901KL3 als sporadic 60956 51771 5372 3807
answerals CASE_NEUBC998WWB als sqstm1 59342 50924 4598 3813
answerals CASE_NEUBD218YR3 als fig4 56370 48129 4615 3614
answerals CASE_NEUBD288RXQ als sporadic 55161 47418 4097 3639
answerals CASE_NEUBK117YXL als sporadic 59463 51145 4665 3643
answerals CASE_NEUBM949LA5 als sporadic 58583 50142 4614 3812
answerals CASE_NEUBN979ZZ5 als sporadic 61495 52837 4928 3722
answerals CASE_NEUBT273FH3 als sporadic 56265 48124 4487 3646
answerals CASE_NEUBW008RJ5 als sporadic 61206 52495 4727 3979
answerals CASE_NEUBY734PFR als sporadic 55299 47536 4173 3585
answerals CASE_NEUCB613CA9 als sporadic 58135 49890 4495 3741
answerals CASE_NEUCD502BFU als sod1 60442 51808 4904 3719
answerals CASE_NEUCE965ZGK als c9orf72 57625 49386 4460 3771
answerals CASE_NEUCF538BRM als sporadic 58487 49990 4721 3769
answerals CASE_NEUCG511MJ6 als sporadic 61314 52448 5018 3828
answerals CASE_NEUCN596RR3 als sporadic 57637 49881 4177 3570
answerals CASE_NEUCP218XVV als sporadic 62812 54049 4920 3829
answerals CASE_NEUCT022VTK als sporadic 60493 51793 4646 4042
answerals CASE_NEUCT842RJV als sod1 58214 49653 4894 3657
answerals CASE_NEUCU076ADN als sporadic 61936 53586 4432 3905
answerals CASE_NEUCU245GBQ als sporadic 55305 47118 4599 3578
answerals CASE_NEUCV578DFJ als sporadic 56700 48860 4347 3484
answerals CASE_NEUDD018KAH als sporadic 55104 47304 4203 3584
answerals CASE_NEUDG000ZG5 als sporadic 57075 49593 3882 3597
answerals CASE_NEUDG272XWC als sporadic 57736 49728 4263 3738
answerals CASE_NEUDH063DEA als sporadic 56071 47885 4555 3621
answerals CASE_NEUDM949BAR als sporadic 69775 60555 4968 4236
answerals CASE_NEUDP155HFH als sporadic 60357 51432 4971 3944
answerals CASE_NEUDT709YHN als c9orf72 56328 48912 3862 3550
answerals CASE_NEUDY534KGP als sporadic 60624 51916 4824 3870
answerals CASE_NEUDZ473EGM als c9orf72 61242 52126 5334 3775
answerals CASE_NEUEB422WW0 als sporadic 60128 51463 4794 3861
answerals CASE_NEUEC400NYR als setx 59892 51429 4475 3977
answerals CASE_NEUEK191WYC als sporadic 57379 49199 4465 3707
answerals CASE_NEUEM029XXZ als sporadic 56477 48694 4220 3552
answerals CASE_NEUEM720BUU als c9orf72 54756 46712 4925 3114
answerals CASE_NEUEN017PCJ als sporadic 59090 50634 4675 3777
answerals CASE_NEUEN476CLW als c9orf72 57817 49656 4548 3610
answerals CASE_NEUET072VDG als sporadic 60255 51758 4671 3822
answerals CASE_NEUEU318NY2 als sporadic 59240 50849 4534 3848
answerals CASE_NEUEU558MNK als sporadic 57011 48900 4349 3756
answerals CASE_NEUEY478NZP als sod1 60025 51188 4967 3857
answerals CASE_NEUFB989DT1 als sporadic 57424 49535 4190 3690
answerals CASE_NEUFH122WN7 als sqstm1 60603 52149 4532 3907
answerals CASE_NEUFH461AAN als sporadic 68843 59569 4938 4322
answerals CASE_NEUFU395MJD als sporadic 56093 48085 4401 3600
answerals CASE_NEUFV237VCZ als c9orf72 56842 48626 4510 3700
answerals CASE_NEUFX386KMB als sporadic 58198 49094 5283 3813
answerals CASE_NEUFY342UNG als sporadic 58116 50159 4073 3874
answerals CASE_NEUGD965XVD als sporadic 60862 52133 4767 3955
answerals CASE_NEUGE540TC4 als sporadic 53921 46403 4014 3495
answerals CASE_NEUGH995TFK als c9orf72 61513 52988 4649 3868
answerals CASE_NEUGJ081HKR als c9orf72 55208 47517 4172 3514
answerals CASE_NEUGL543NJ1 als sporadic 57839 49612 4487 3733
answerals CASE_NEUGP781PDU als sporadic 56686 48624 4368 3685
answerals CASE_NEUGR121TFD als sporadic 69750 60168 5084 4486
answerals CASE_NEUGR539MVT als sporadic 58504 50015 4595 3881
answerals CASE_NEUGW326BRV als sporadic 52833 45536 4027 3265
answerals CASE_NEUGW340YEB als sporadic 60711 52631 4259 3810
answerals CASE_NEUHB491NGF als sporadic 58510 50251 4430 3820
answerals CASE_NEUHG644RYB als sporadic 59879 51759 4296 3816
answerals CASE_NEUHG791RV5 als sporadic 56657 48931 4109 3614
answerals CASE_NEUHK991AVP als sod1 57556 49162 4595 3790
answerals CASE_NEUHL999WWT als sporadic 57573 49110 4678 3779
answerals CASE_NEUHM532NDD als sporadic 60699 52285 4581 3828
answerals CASE_NEUHT569HT1 als sporadic 62072 53367 4747 3951
answerals CASE_NEUHV216EHA als sporadic 57938 49858 4351 3717
answerals CASE_NEUHW530WD8 als sporadic 60842 52228 4727 3878
answerals CASE_NEUHW590KBH als sporadic 54091 46700 4011 3373
answerals CASE_NEUHY206ZEQ als sporadic 55933 47862 4431 3626
answerals CASE_NEUHZ302VU4 als sporadic 53741 46046 4170 3519
answerals CASE_NEUJA217MTJ als sporadic 59038 51588 3935 3508
answerals CASE_NEUJA666PYD als sporadic 57285 49098 4458 3718
answerals CASE_NEUJC191RLE als pfn1 57936 49894 4339 3693
answerals CASE_NEUJG311WGV als sporadic 57839 49407 4710 3712
answerals CASE_NEUJG885PY7 als sporadic 60245 51768 4580 3889
answerals CASE_NEUJH197AK2 als sporadic 58104 49709 4666 3720
answerals CASE_NEUJK720JCL als sporadic 63459 53214 6353 3879
answerals CASE_NEUJL547WVQ als sporadic 66479 58462 3618 4387
answerals CASE_NEUJL595JAZ als sporadic 68444 59292 4865 4278
answerals CASE_NEUJP935AVF als sporadic 58826 50443 4557 3815
answerals CASE_NEUJX780XXK als sporadic 58759 50213 4626 3913
answerals CASE_NEUJX990GR5 als c9orf72 62532 53432 5134 3957
answerals CASE_NEUJY426MBU als sporadic 63184 53940 5247 3990
answerals CASE_NEUJY536DKF als sporadic 58841 50172 4803 3859
answerals CASE_NEUKA860NUG als sporadic 57475 49594 4413 3465
answerals CASE_NEUKD025JPF als sporadic 53032 45368 4160 3495
answerals CASE_NEUKP160HX8 als sporadic 60955 52292 4709 3940
answerals CASE_NEUKR376CW3 als sporadic 59716 51083 4859 3767
answerals CASE_NEUKV547CFA als sporadic 58332 50402 4378 3545
answerals CASE_NEUKY704JVA als sporadic 57919 49881 4214 3817
answerals CASE_NEULA694DDC als sporadic 56553 48081 4925 3538
answerals CASE_NEULA777DBT als sporadic 60828 52252 4780 3788
answerals CASE_NEULD354RZB als sporadic 58571 50309 4500 3756
answerals CASE_NEULH729AU2 als sporadic 56790 48811 4431 3540
answerals CASE_NEULL588ALG als sporadic 58040 50064 4307 3660
answerals CASE_NEULL648LJ1 als sporadic 59952 51253 4757 3931
answerals CASE_NEULP998KDJ als sporadic 55783 48072 3973 3727
answerals CASE_NEULT851ENP als sporadic 57842 49090 4970 3777
answerals CASE_NEULY177TTN als sporadic 54390 46686 4203 3497
answerals CASE_NEULY328CRJ als sporadic 57720 49451 4533 3729
answerals CASE_NEULZ548ZXV als sporadic 68624 59417 4897 4298
answerals CASE_NEUMB242CLN als sporadic 64129 55161 5047 3916
answerals CASE_NEUME498PCJ als sporadic 58309 50715 3999 3585
answerals CASE_NEUMH634MKT als sporadic 60658 51952 4866 3832
answerals CASE_NEUMN012EVP als sporadic 58561 50094 4680 3778
answerals CASE_NEUMW598YMT als sporadic 62333 53419 5026 3878
answerals CASE_NEUMY871DGF als sporadic 60697 51759 5020 3907
answerals CASE_NEUNA248WXL als sporadic 55051 47376 4045 3621
answerals CASE_NEUNG326MFP als sporadic 61248 52461 4840 3937
answerals CASE_NEUNJ155KYL als sporadic 60514 51907 4617 3984
answerals CASE_NEUNJ938DUL als sporadic 59969 51779 4561 3625
answerals CASE_NEUNL303HLF als sporadic 56991 48903 4274 3802
answerals CASE_NEUNL415AFW als c9orf72 57236 49163 4505 3561
answerals CASE_NEUNR020KV6 als sporadic 57657 49284 4569 3797
answerals CASE_NEUNZ171UYF als sporadic 58352 49773 4750 3822
answerals CASE_NEUPG593UTV als sporadic 60219 51623 4928 3658
answerals CASE_NEUPK546ZLD als c9orf72 58822 50244 4762 3809
answerals CASE_NEUPM937TMY als sporadic 56356 48263 4429 3656
answerals CASE_NEUPN525XEW als sporadic 56269 48342 4398 3523
answerals CASE_NEUPR357AUF als sporadic 60436 51732 4868 3825
answerals CASE_NEUPR600MBU als sporadic 55080 47217 4373 3486
answerals CASE_NEUPY050ANK als sporadic 59160 50401 5042 3705
answerals CASE_NEURA639MK8 als sporadic 53531 46259 3799 3464
answerals CASE_NEURF720KHA als sporadic 57317 49163 4440 3708
answerals CASE_NEURJ362MXH als setx 57101 49137 4246 3708
answerals CASE_NEURR881FKY als sporadic 56549 48837 4135 3570
answerals CASE_NEURX315DYH als sporadic 57026 48201 5162 3652
answerals CASE_NEURX909UL6 als sporadic 57249 48874 4767 3599
answerals CASE_NEUTA057AF6 als sod1 63145 54036 5095 3999
answerals CASE_NEUTA689LN5 als sporadic 57830 49621 4555 3644
answerals CASE_NEUTB230DA3 als sporadic 68334 58838 5088 4393
answerals CASE_NEUTC791PVE als sporadic 64212 55029 5293 3881
answerals CASE_NEUTD314VFT als sporadic 58647 50159 4656 3823
answerals CASE_NEUTD713DE3 als sporadic 56983 48958 4482 3534
answerals CASE_NEUTD866EAH als sporadic 70740 60910 5440 4375
answerals CASE_NEUTJ613AH9 als sporadic 53539 45913 4221 3399
answerals CASE_NEUTL257PNR als sporadic 57838 49524 4614 3687
answerals CASE_NEUTL699WJ0 als sporadic 60387 51630 4950 3799
answerals CASE_NEUTM934BPY als sporadic 60947 51341 5935 3661
answerals CASE_NEUTN952DDG als c9orf72 56066 48151 4328 3580
answerals CASE_NEUTU360YJY als sporadic 59112 50447 4749 3908
answerals CASE_NEUUC458RFT als c9orf72 61553 53233 4547 3765
answerals CASE_NEUUD158CJF als sporadic 59508 50942 4824 3730
answerals CASE_NEUUE852BB1 als sporadic 56400 48072 4698 3619
answerals CASE_NEUUF613PHL als sporadic 55668 47492 4621 3545
answerals CASE_NEUUH658EYH als sporadic 67044 57942 4822 4271
answerals CASE_NEUUJ507EAB als sporadic 58926 51621 3506 3788
answerals CASE_NEUUL256UC9 als c9orf72 58166 50041 4368 3743
answerals CASE_NEUUL292XRC als sporadic 59515 51097 4721 3686
answerals CASE_NEUUL311NRQ als sporadic 57975 49431 4783 3749
answerals CASE_NEUUP280KXL als sporadic 58169 49874 4518 3770
answerals CASE_NEUUU506WZF als sporadic 59501 50857 4906 3733
answerals CASE_NEUUZ216XY8 als sporadic 61825 52520 5471 3828
answerals CASE_NEUVD687XD8 als sporadic 63026 54907 4313 3796
answerals CASE_NEUVF888UHM als sporadic 54658 47080 4082 3494
answerals CASE_NEUVJ560JGZ als sporadic 60403 51758 4810 3826
answerals CASE_NEUVM674HUA als sporadic 56991 49038 4448 3496
answerals CASE_NEUVN746WKV als sporadic 58209 50322 4279 3598
answerals CASE_NEUVP060WFG als sporadic 58717 50229 4679 3797
answerals CASE_NEUVR636VTP als sporadic 59011 50635 4539 3834
answerals CASE_NEUVR814YCY als sporadic 60715 52433 4462 3810
answerals CASE_NEUVU735HU6 als sporadic 69147 60054 4847 4231
answerals CASE_NEUVV225XKB als sporadic 59317 50646 4759 3901
answerals CASE_NEUVW680LPK als c9orf72 57874 49510 4588 3767
answerals CASE_NEUVW999FP9 als sporadic 59423 51099 4516 3797
answerals CASE_NEUVX902YNL als c9orf72 54908 46768 4417 3720
answerals CASE_NEUWD538KT3 als c9orf72 56245 48044 4604 3589
answerals CASE_NEUWD946RDA als sporadic 62506 53415 5157 3926
answerals CASE_NEUWH380YHV als sporadic 59186 50751 4635 3790
answerals CASE_NEUWH955FJF als sporadic 61047 52562 4604 3873
answerals CASE_NEUWJ389FC7 als sporadic 57396 49162 4466 3759
answerals CASE_NEUWM344ZLM als sod1 55629 47637 4284 3703
answerals CASE_NEUWP426NBR als sporadic 57165 49264 4286 3605
answerals CASE_NEUWX167DAH als sporadic 58440 50098 4519 3815
answerals CASE_NEUWY079WUH als sporadic 66375 56843 5286 4234
answerals CASE_NEUWZ614ARQ als sporadic 54933 46815 4446 3664
answerals CASE_NEUXD985ZU1 als sporadic 59705 51105 4765 3824
answerals CASE_NEUXE491RMM als sporadic 55908 48343 3994 3565
answerals CASE_NEUXG265ME9 als sporadic 58728 50395 4414 3905
answerals CASE_NEUXH833LL4 als sporadic 59041 50605 4621 3805
answerals CASE_NEUXP289KRC als sod1 57123 48766 4667 3684
answerals CASE_NEUXP495XE2 als sporadic 59608 51399 4358 3842
answerals CASE_NEUXP595FFP als sporadic 53531 45773 4199 3551
answerals CASE_NEUXV122FN3 als sporadic 61048 52398 4683 3955
answerals CASE_NEUXX361RUG als sporadic 55793 48069 4188 3530
answerals CASE_NEUYC055XPZ als sporadic 57919 49334 4796 3776
answerals CASE_NEUYC303AJY als sporadic 58961 50283 4820 3846
answerals CASE_NEUYD306HAB als sporadic 58116 49543 5005 3556
answerals CASE_NEUYG208KVV als sporadic 56507 48381 4375 3744
answerals CASE_NEUYG298CA9 als sporadic 60406 51438 5148 3813
answerals CASE_NEUYH924UCE als sporadic 60296 51515 4748 4023
answerals CASE_NEUYJ705VN9 als sporadic 60720 52113 4782 3815
answerals CASE_NEUYK029WUU als sporadic 55198 47101 4462 3624
answerals CASE_NEUYL008GM4 als sporadic 57699 49865 4109 3717
answerals CASE_NEUYL149PRF als sporadic 56637 48855 4120 3655
answerals CASE_NEUYP226CPW als sporadic 61950 53333 4720 3886
answerals CASE_NEUYP235ZLD als tardbp 56820 48881 4254 3675
answerals CASE_NEUYT193FFG als sporadic 58074 49545 4676 3843
answerals CASE_NEUYY225MNZ als c9orf72 53495 46046 3923 3522
answerals CASE_NEUYY614DN8 als sporadic 62481 53489 5170 3811
answerals CASE_NEUYY878JGP als sporadic 60999 52371 4890 3730
answerals CASE_NEUZD231YZ6 als sporadic 54797 46712 4520 3555
answerals CASE_NEUZE432DZM als sporadic 61125 52221 5070 3824
answerals CASE_NEUZF321EW4 als sod1 57596 49433 4445 3714
answerals CASE_NEUZF473UEP als sporadic 64617 55405 5175 4030
answerals CASE_NEUZJ053JGZ als sporadic 59197 50800 4539 3853
answerals CASE_NEUZK054DP5 als sporadic 58652 50511 4362 3769
answerals CASE_NEUZN836GME als sporadic 60499 51754 4899 3836
answerals CASE_NEUZN936HJ9 als sporadic 55162 47141 4250 3767
answerals CASE_NEUZP278MR4 als sporadic 58249 49800 4552 3889
answerals CASE_NEUZT557DHF als sporadic 59667 51310 4558 3792
answerals CASE_NEUZT902WVB als sporadic 63471 54337 4965 4155
answerals CASE_NEUZV656DD1 als sporadic 69727 60051 5192 4473
answerals CASE_NEUZW701NNF als c9orf72 54607 46701 4364 3535
answerals CASE_NEUZX521TKK als sporadic 56578 48274 4694 3604
answerals CASE_NEUZX847VWV als sporadic 58281 49775 4672 3831
answerals CASE_NEUZY128BJ2 als sporadic 63551 54316 5192 4036
answerals CASE_NEUZY975XKL als sporadic 57443 49428 4230 3778
answerals CTRL_NEUAA485DZL ctrl ctrl 63238 54544 4780 3909
answerals CTRL_NEUAJ025JC3 ctrl ctrl 56132 48574 4080 3466
answerals CTRL_NEUAJ928PAA ctrl ctrl 58615 50164 4733 3710
answerals CTRL_NEUCA748GF2 ctrl ctrl 57039 48969 4365 3699
answerals CTRL_NEUCV136DHM ctrl ctrl 60751 51891 4924 3924
answerals CTRL_NEUCV809LL4 ctrl ctrl 53289 45860 4098 3323
answerals CTRL_NEUDA782GW3 ctrl ctrl 57198 49513 4260 3415
answerals CTRL_NEUDE949BP3 ctrl ctrl 57359 49426 4398 3529
answerals CTRL_NEUDM126GNG ctrl ctrl 59261 50526 4954 3766
answerals CTRL_NEUDT762KUL ctrl ctrl 55473 47767 4227 3468
answerals CTRL_NEUEB210XRC ctrl ctrl 57704 49296 4689 3707
answerals CTRL_NEUEY565NWT ctrl ctrl 56602 48391 4712 3489
answerals CTRL_NEUFL733GX5 ctrl ctrl 64451 54811 5716 3914
answerals CTRL_NEUFZ500KDB ctrl ctrl 57073 48888 4595 3581
answerals CTRL_NEUFZ508VBV ctrl ctrl 53898 46830 3735 3326
answerals CTRL_NEUHE723FGT ctrl ctrl 58113 50153 4255 3694
answerals CTRL_NEUHZ716BZ2 ctrl ctrl 54109 46540 4156 3404
answerals CTRL_NEUJH290RH7 ctrl ctrl 53571 46469 3731 3367
answerals CTRL_NEUJX341NDP ctrl ctrl 53093 45615 4041 3427
answerals CTRL_NEUKW131XJ2 ctrl ctrl 55174 47339 4338 3490
answerals CTRL_NEULL933JXY ctrl ctrl 57664 49898 4032 3723
answerals CTRL_NEUMA002VLD ctrl ctrl 59949 51244 4686 4011
answerals CTRL_NEUMF089KLV ctrl ctrl 56930 48697 4475 3751
answerals CTRL_NEUML507PFJ ctrl ctrl 55269 47121 4524 3616
answerals CTRL_NEUMN061ATZ ctrl ctrl 53189 45465 4159 3552
answerals CTRL_NEUMT184NWC ctrl ctrl 60108 51580 4731 3791
answerals CTRL_NEUNC876ZB2 ctrl ctrl 61491 52926 4499 4057
answerals CTRL_NEUNN472ACB ctrl ctrl 69191 59326 5702 4149
answerals CTRL_NEUNW343RXP ctrl ctrl 55652 47504 4485 3657
answerals CTRL_NEUPH301NNX ctrl ctrl 54521 47158 3958 3397
answerals CTRL_NEUPL878MTL ctrl ctrl 58345 50015 4518 3804
answerals CTRL_NEUPW536ZKZ ctrl ctrl 58923 50330 4811 3771
answerals CTRL_NEURJ861MMD ctrl ctrl 58755 51011 4136 3605
answerals CTRL_NEURV546WMW ctrl ctrl 61817 53187 4606 4015
answerals CTRL_NEUUV825HYF ctrl ctrl 54032 46512 4121 3389
answerals CTRL_NEUVZ050YX7 ctrl ctrl 54408 46947 4018 3437
answerals CTRL_NEUWN092BVG ctrl ctrl 56657 48926 3971 3752
answerals CTRL_NEUWT164JRQ ctrl ctrl 58778 50113 4861 3794
answerals CTRL_NEUXC258VTR ctrl ctrl 61355 52769 4716 3859
answerals CTRL_NEUXP955XW7 ctrl ctrl 58954 50522 4798 3628
answerals CTRL_NEUXW311EFC ctrl ctrl 53050 45720 3940 3384
answerals CTRL_NEUYM205MRL ctrl ctrl 58659 50854 4064 3734

Table S9 Gene fusions per sample

ipsc_mn_als_datasets.starfusion.n = ipsc_mn_als_datasets.starfusion %>% 
  add_count(dataset_sample) %>% # count number of fusions per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset, sample, condition, fusion_number = n, total_reads, dataset_sample, mutation) #keep 1 row per sample
 # add samples with 0 fusions
ipsc_mn_als_datasets.starfusion.samples_no_fusions = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% ipsc_mn_als_datasets.starfusion.n$dataset_sample] 
ipsc_mn_als_datasets.paired_end.metadata.no_fusions = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% ipsc_mn_als_datasets.starfusion.samples_no_fusions) %>% 
  left_join(multiqc_rseqc_read_distribution.tsv) %>%
  mutate(fusion_number = 0) %>% select(dataset_sample, sample, fusion_number, condition, dataset, total_reads, mutation)
ipsc_mn_als_datasets.starfusion.n = bind_rows(ipsc_mn_als_datasets.starfusion.n, ipsc_mn_als_datasets.paired_end.metadata.no_fusions)
ipsc_mn_als_datasets.starfusion.table_s9 = ipsc_mn_als_datasets.starfusion.n %>% select(dataset, sample, condition, mutation, fusion_number, total_reads)
kbl(ipsc_mn_als_datasets.starfusion.table_s9) %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), fixed_thead = T) %>% scroll_box(width = "100%", height = "500px")
dataset sample condition mutation fusion_number total_reads
answerals CASE_NEUDE902GCT als c9orf72 13 80351595
answerals CTRL_NEUAA485DZL ctrl ctrl 6 92629631
answerals CASE_NEUAA599TMX als sporadic 6 77223828
answerals CASE_NEUAB000NKC als c9orf72 31 71106777
answerals CASE_NEUAE228FF6 als sporadic 2 63533855
answerals CASE_NEUAE993EPR als sporadic 9 93223837
answerals CASE_NEUAF553MJ3 als sporadic 8 92294028
answerals CASE_NEUAG241NUD als sporadic 7 88487027
answerals CASE_NEUAG603XLK als pfn1 11 41359233
answerals CASE_NEUAG766ULB als sporadic 12 85338776
answerals CTRL_NEUAJ025JC3 ctrl ctrl 15 78856459
answerals CTRL_NEUAJ928PAA ctrl ctrl 16 96697354
answerals CASE_NEUAL076FCE als sporadic 12 88517839
answerals CASE_NEUAM655HF7 als sporadic 12 70099172
answerals CASE_NEUAP285GGU als sporadic 15 71653943
answerals CASE_NEUAT234RK6 als sporadic 14 86690836
answerals CASE_NEUAW157NMJ als sporadic 25 94641466
answerals CASE_NEUAW717TN6 als sporadic 8 96444518
answerals CASE_NEUAX665ZHY als sporadic 11 96375698
answerals CASE_NEUAY067UTB als chchd1 14 103940017
answerals CASE_NEUAZ394JEZ als sporadic 7 90298769
answerals CASE_NEUBA169GXD als sporadic 13 90044591
answerals CASE_NEUBC901KL3 als sporadic 11 96083124
answerals CASE_NEUBC998WWB als sqstm1 11 97383223
answerals CASE_NEUBD218YR3 als fig4 19 72915834
answerals CASE_NEUBD288RXQ als sporadic 10 92088313
answerals CASE_NEUBK117YXL als sporadic 21 92338200
answerals CASE_NEUBM949LA5 als sporadic 9 86250060
answerals CASE_NEUBN979ZZ5 als sporadic 4 89827770
answerals CASE_NEUBT273FH3 als sporadic 17 74542618
answerals CASE_NEUBW008RJ5 als sporadic 14 106645947
answerals CASE_NEUBY734PFR als sporadic 6 74456844
answerals CTRL_NEUCA748GF2 ctrl ctrl 8 82008988
answerals CASE_NEUCB613CA9 als sporadic 9 90541534
answerals CASE_NEUCD502BFU als sod1 9 89586112
answerals CASE_NEUCE965ZGK als c9orf72 20 78627760
answerals CASE_NEUCF538BRM als sporadic 7 97574144
answerals CASE_NEUCG511MJ6 als sporadic 6 98813421
answerals CASE_NEUCN596RR3 als sporadic 5 89512093
answerals CASE_NEUCP218XVV als sporadic 12 93789222
answerals CASE_NEUCT022VTK als sporadic 11 100874817
answerals CASE_NEUCT842RJV als sod1 26 86138539
answerals CASE_NEUCU076ADN als sporadic 6 95677719
answerals CASE_NEUCU245GBQ als sporadic 12 72116830
answerals CTRL_NEUCV136DHM ctrl ctrl 10 96543719
answerals CASE_NEUCV578DFJ als sporadic 10 72026572
answerals CTRL_NEUCV809LL4 ctrl ctrl 19 60185905
answerals CTRL_NEUDA782GW3 ctrl ctrl 16 71137627
answerals CASE_NEUDD018KAH als sporadic 14 70760037
answerals CTRL_NEUDE949BP3 ctrl ctrl 18 84067732
answerals CASE_NEUDG000ZG5 als sporadic 13 79910862
answerals CASE_NEUDG272XWC als sporadic 10 82329332
answerals CASE_NEUDH063DEA als sporadic 8 66730587
answerals CTRL_NEUDM126GNG ctrl ctrl 12 89281476
answerals CASE_NEUDM949BAR als sporadic 9 79446358
answerals CASE_NEUDP155HFH als sporadic 8 104761280
answerals CASE_NEUDT709YHN als c9orf72 6 80752554
answerals CTRL_NEUDT762KUL ctrl ctrl 17 68969167
answerals CASE_NEUDY534KGP als sporadic 10 91012561
answerals CASE_NEUDZ473EGM als c9orf72 10 112302126
answerals CTRL_NEUEB210XRC ctrl ctrl 10 83801109
answerals CASE_NEUEB422WW0 als sporadic 18 102960267
answerals CASE_NEUEC400NYR als setx 7 92373132
answerals CASE_NEUEK191WYC als sporadic 9 84425639
answerals CASE_NEUEM029XXZ als sporadic 14 77394197
answerals CASE_NEUEM720BUU als c9orf72 39 63755467
answerals CASE_NEUEN017PCJ als sporadic 10 90774153
answerals CASE_NEUEN476CLW als c9orf72 21 76588865
answerals CASE_NEUET072VDG als sporadic 15 95322550
answerals CASE_NEUEU318NY2 als sporadic 13 91271120
answerals CASE_NEUEU558MNK als sporadic 13 83207564
answerals CASE_NEUEY478NZP als sod1 13 83363466
answerals CTRL_NEUEY565NWT ctrl ctrl 10 82690328
answerals CASE_NEUFB989DT1 als sporadic 6 80810272
answerals CASE_NEUFH122WN7 als sqstm1 5 108588802
answerals CASE_NEUFH461AAN als sporadic 20 95778777
answerals CTRL_NEUFL733GX5 ctrl ctrl 6 94018469
answerals CASE_NEUFU395MJD als sporadic 11 72993028
answerals CASE_NEUFV237VCZ als c9orf72 20 89352295
answerals CASE_NEUFX386KMB als sporadic 9 96918010
answerals CASE_NEUFY342UNG als sporadic 10 90963548
answerals CTRL_NEUFZ500KDB ctrl ctrl 11 85044761
answerals CTRL_NEUFZ508VBV ctrl ctrl 8 75909259
answerals CASE_NEUGD965XVD als sporadic 5 103651614
answerals CASE_NEUGE540TC4 als sporadic 11 64036466
answerals CASE_NEUGH995TFK als c9orf72 7 85349248
answerals CASE_NEUGJ081HKR als c9orf72 8 75455646
answerals CASE_NEUGL543NJ1 als sporadic 9 92931442
answerals CASE_NEUGP781PDU als sporadic 10 80833254
answerals CASE_NEUGR121TFD als sporadic 15 102872584
answerals CASE_NEUGR539MVT als sporadic 7 94175062
answerals CASE_NEUGW326BRV als sporadic 18 69987454
answerals CASE_NEUGW340YEB als sporadic 15 98422534
answerals CASE_NEUHB491NGF als sporadic 12 105880561
answerals CTRL_NEUHE723FGT ctrl ctrl 13 98431529
answerals CASE_NEUHG644RYB als sporadic 9 96700132
answerals CASE_NEUHG791RV5 als sporadic 15 93752450
answerals CASE_NEUHK991AVP als sod1 12 95449413
answerals CASE_NEUHL999WWT als sporadic 11 91645541
answerals CASE_NEUHM532NDD als sporadic 12 97995986
answerals CASE_NEUHT569HT1 als sporadic 7 97925023
answerals CASE_NEUHV216EHA als sporadic 10 100671641
answerals CASE_NEUHW530WD8 als sporadic 16 105977870
answerals CASE_NEUHW590KBH als sporadic 10 72181419
answerals CASE_NEUHY206ZEQ als sporadic 18 74090361
answerals CASE_NEUHZ302VU4 als sporadic 13 67530789
answerals CTRL_NEUHZ716BZ2 ctrl ctrl 13 71207355
answerals CASE_NEUJA217MTJ als sporadic 6 115185396
answerals CASE_NEUJA666PYD als sporadic 19 80935095
answerals CASE_NEUJC191RLE als pfn1 8 101473499
answerals CASE_NEUJG311WGV als sporadic 10 90925131
answerals CASE_NEUJG885PY7 als sporadic 13 98116859
answerals CASE_NEUJH197AK2 als sporadic 20 77814469
answerals CTRL_NEUJH290RH7 ctrl ctrl 6 66856215
answerals CASE_NEUJK720JCL als sporadic 6 106522739
answerals CASE_NEUJL547WVQ als sporadic 7 86686484
answerals CASE_NEUJL595JAZ als sporadic 16 85731672
answerals CASE_NEUJP935AVF als sporadic 7 88750101
answerals CTRL_NEUJX341NDP ctrl ctrl 7 71651755
answerals CASE_NEUJX780XXK als sporadic 5 100118041
answerals CASE_NEUJX990GR5 als c9orf72 2 112621195
answerals CASE_NEUJY426MBU als sporadic 6 122500065
answerals CASE_NEUJY536DKF als sporadic 10 98537826
answerals CASE_NEUKA860NUG als sporadic 15 62840884
answerals CASE_NEUKD025JPF als sporadic 12 60919280
answerals CASE_NEUKP160HX8 als sporadic 12 102003991
answerals CASE_NEUKR376CW3 als sporadic 12 97538990
answerals CASE_NEUKV547CFA als sporadic 12 69364009
answerals CTRL_NEUKW131XJ2 ctrl ctrl 17 74096752
answerals CASE_NEUKY704JVA als sporadic 9 80410172
answerals CASE_NEULA694DDC als sporadic 10 72567703
answerals CASE_NEULA777DBT als sporadic 18 110522400
answerals CASE_NEULD354RZB als sporadic 12 92499799
answerals CASE_NEULH729AU2 als sporadic 8 66477122
answerals CASE_NEULL588ALG als sporadic 7 83847300
answerals CASE_NEULL648LJ1 als sporadic 14 110155878
answerals CTRL_NEULL933JXY ctrl ctrl 7 82671867
answerals CASE_NEULP998KDJ als sporadic 8 77194450
answerals CASE_NEULT851ENP als sporadic 7 99055975
answerals CASE_NEULY177TTN als sporadic 17 67915998
answerals CASE_NEULY328CRJ als sporadic 13 84555017
answerals CASE_NEULZ548ZXV als sporadic 20 83302460
answerals CTRL_NEUMA002VLD ctrl ctrl 6 93511645
answerals CASE_NEUMB242CLN als sporadic 14 104455218
answerals CASE_NEUME498PCJ als sporadic 7 93041938
answerals CTRL_NEUMF089KLV ctrl ctrl 7 77138477
answerals CASE_NEUMH634MKT als sporadic 12 101656984
answerals CTRL_NEUML507PFJ ctrl ctrl 8 68142265
answerals CASE_NEUMN012EVP als sporadic 8 95638539
answerals CTRL_NEUMN061ATZ ctrl ctrl 12 77105679
answerals CTRL_NEUMT184NWC ctrl ctrl 12 92838742
answerals CASE_NEUMW598YMT als sporadic 10 100036715
answerals CASE_NEUMY871DGF als sporadic 5 109363694
answerals CASE_NEUNA248WXL als sporadic 7 73992295
answerals CTRL_NEUNC876ZB2 ctrl ctrl 6 83265656
answerals CASE_NEUNG326MFP als sporadic 7 100565728
answerals CASE_NEUNJ155KYL als sporadic 7 95718335
answerals CASE_NEUNJ938DUL als sporadic 11 75727499
answerals CASE_NEUNL303HLF als sporadic 12 77783363
answerals CASE_NEUNL415AFW als c9orf72 23 72450848
answerals CTRL_NEUNN472ACB ctrl ctrl 15 78003255
answerals CASE_NEUNR020KV6 als sporadic 5 79298369
answerals CTRL_NEUNW343RXP ctrl ctrl 9 67553681
answerals CASE_NEUNZ171UYF als sporadic 5 113844202
answerals CASE_NEUPG593UTV als sporadic 14 81542271
answerals CTRL_NEUPH301NNX ctrl ctrl 12 81219399
answerals CASE_NEUPK546ZLD als c9orf72 16 95071196
answerals CTRL_NEUPL878MTL ctrl ctrl 10 88824097
answerals CASE_NEUPM937TMY als sporadic 16 78296968
answerals CASE_NEUPN525XEW als sporadic 29 77106625
answerals CASE_NEUPR357AUF als sporadic 14 99795776
answerals CASE_NEUPR600MBU als sporadic 12 78140048
answerals CTRL_NEUPW536ZKZ ctrl ctrl 12 90333508
answerals CASE_NEUPY050ANK als sporadic 9 85546543
answerals CASE_NEURA639MK8 als sporadic 17 65451477
answerals CASE_NEURF720KHA als sporadic 13 84067184
answerals CASE_NEURJ362MXH als setx 6 93645424
answerals CTRL_NEURJ861MMD ctrl ctrl 10 100766856
answerals CASE_NEURR881FKY als sporadic 12 86886855
answerals CTRL_NEURV546WMW ctrl ctrl 13 111102498
answerals CASE_NEURX315DYH als sporadic 10 73562711
answerals CASE_NEURX909UL6 als sporadic 19 79097478
answerals CASE_NEUTA057AF6 als sod1 12 108681404
answerals CASE_NEUTA689LN5 als sporadic 19 78200437
answerals CASE_NEUTB230DA3 als sporadic 13 89915287
answerals CASE_NEUTC791PVE als sporadic 14 97793523
answerals CASE_NEUTD314VFT als sporadic 9 85036873
answerals CASE_NEUTD713DE3 als sporadic 19 86563683
answerals CASE_NEUTD866EAH als sporadic 6 83462831
answerals CASE_NEUTJ613AH9 als sporadic 6 60785280
answerals CASE_NEUTL257PNR als sporadic 11 92252300
answerals CASE_NEUTL699WJ0 als sporadic 8 84089003
answerals CASE_NEUTM934BPY als sporadic 5 95659466
answerals CASE_NEUTN952DDG als c9orf72 25 81390541
answerals CASE_NEUTU360YJY als sporadic 21 86008260
answerals CASE_NEUUC458RFT als c9orf72 7 85257121
answerals CASE_NEUUD158CJF als sporadic 4 73223524
answerals CASE_NEUUE852BB1 als sporadic 17 69679811
answerals CASE_NEUUF613PHL als sporadic 9 88686748
answerals CASE_NEUUH658EYH als sporadic 13 79107840
answerals CASE_NEUUJ507EAB als sporadic 5 80476943
answerals CASE_NEUUL256UC9 als c9orf72 10 91609649
answerals CASE_NEUUL292XRC als sporadic 10 72128909
answerals CASE_NEUUL311NRQ als sporadic 9 100591313
answerals CASE_NEUUP280KXL als sporadic 9 88847741
answerals CASE_NEUUU506WZF als sporadic 3 91100217
answerals CTRL_NEUUV825HYF ctrl ctrl 9 70624857
answerals CASE_NEUUZ216XY8 als sporadic 12 84742547
answerals CASE_NEUVD687XD8 als sporadic 13 85203015
answerals CASE_NEUVF888UHM als sporadic 22 70783470
answerals CASE_NEUVJ560JGZ als sporadic 8 115247071
answerals CASE_NEUVM674HUA als sporadic 36 82820866
answerals CASE_NEUVN746WKV als sporadic 27 84953195
answerals CASE_NEUVP060WFG als sporadic 9 96612825
answerals CASE_NEUVR636VTP als sporadic 15 95352910
answerals CASE_NEUVR814YCY als sporadic 10 104088826
answerals CASE_NEUVU735HU6 als sporadic 11 84591201
answerals CASE_NEUVV225XKB als sporadic 13 88170541
answerals CASE_NEUVW680LPK als c9orf72 14 87448426
answerals CASE_NEUVW999FP9 als sporadic 11 88473708
answerals CASE_NEUVX902YNL als c9orf72 5 81243471
answerals CTRL_NEUVZ050YX7 ctrl ctrl 7 77251633
answerals CASE_NEUWD538KT3 als c9orf72 18 74315992
answerals CASE_NEUWD946RDA als sporadic 8 102258678
answerals CASE_NEUWH380YHV als sporadic 6 90420294
answerals CASE_NEUWH955FJF als sporadic 6 91413950
answerals CASE_NEUWJ389FC7 als sporadic 8 88864871
answerals CASE_NEUWM344ZLM als sod1 9 80462242
answerals CTRL_NEUWN092BVG ctrl ctrl 7 74745103
answerals CASE_NEUWP426NBR als sporadic 12 85098806
answerals CTRL_NEUWT164JRQ ctrl ctrl 9 103798428
answerals CASE_NEUWX167DAH als sporadic 5 87911909
answerals CASE_NEUWY079WUH als sporadic 10 75802121
answerals CASE_NEUWZ614ARQ als sporadic 10 72558498
answerals CTRL_NEUXC258VTR ctrl ctrl 15 103588765
answerals CASE_NEUXD985ZU1 als sporadic 8 92604037
answerals CASE_NEUXE491RMM als sporadic 9 82047541
answerals CASE_NEUXG265ME9 als sporadic 10 93938146
answerals CASE_NEUXH833LL4 als sporadic 16 98829108
answerals CASE_NEUXP289KRC als sod1 11 106091617
answerals CASE_NEUXP495XE2 als sporadic 13 100629256
answerals CASE_NEUXP595FFP als sporadic 10 67304414
answerals CTRL_NEUXP955XW7 ctrl ctrl 8 82124112
answerals CASE_NEUXV122FN3 als sporadic 11 93817112
answerals CTRL_NEUXW311EFC ctrl ctrl 8 56004456
answerals CASE_NEUXX361RUG als sporadic 17 87796977
answerals CASE_NEUYC055XPZ als sporadic 8 100062178
answerals CASE_NEUYC303AJY als sporadic 3 86066890
answerals CASE_NEUYD306HAB als sporadic 12 70161401
answerals CASE_NEUYG208KVV als sporadic 8 80960435
answerals CASE_NEUYG298CA9 als sporadic 9 87861391
answerals CASE_NEUYH924UCE als sporadic 12 89527986
answerals CASE_NEUYJ705VN9 als sporadic 12 83023955
answerals CASE_NEUYK029WUU als sporadic 11 72565571
answerals CASE_NEUYL008GM4 als sporadic 6 96506969
answerals CASE_NEUYL149PRF als sporadic 24 85694260
answerals CTRL_NEUYM205MRL ctrl ctrl 17 89833971
answerals CASE_NEUYP226CPW als sporadic 5 95899428
answerals CASE_NEUYP235ZLD als tardbp 22 85518723
answerals CASE_NEUYT193FFG als sporadic 6 95425283
answerals CASE_NEUYY225MNZ als c9orf72 6 72067964
answerals CASE_NEUYY614DN8 als sporadic 9 94478114
answerals CASE_NEUYY878JGP als sporadic 21 97959785
answerals CASE_NEUZD231YZ6 als sporadic 10 62725001
answerals CASE_NEUZE432DZM als sporadic 3 89658284
answerals CASE_NEUZF321EW4 als sod1 13 88877063
answerals CASE_NEUZF473UEP als sporadic 9 80160194
answerals CASE_NEUZJ053JGZ als sporadic 11 90808999
answerals CASE_NEUZK054DP5 als sporadic 10 84338071
answerals CASE_NEUZN836GME als sporadic 18 107877753
answerals CASE_NEUZN936HJ9 als sporadic 8 61443203
answerals CASE_NEUZP278MR4 als sporadic 13 94669647
answerals CASE_NEUZT557DHF als sporadic 11 86771528
answerals CASE_NEUZT902WVB als sporadic 8 108245336
answerals CASE_NEUZV656DD1 als sporadic 7 106453390
answerals CASE_NEUZW701NNF als c9orf72 10 65392843
answerals CASE_NEUZX521TKK als sporadic 15 76703248
answerals CASE_NEUZX847VWV als sporadic 5 89949563
answerals CASE_NEUZY128BJ2 als sporadic 6 103216328
answerals CASE_NEUZY975XKL als sporadic 12 75377931
neurolincs.diMN 00072034C01 ctrl ctrl 4 88913175
neurolincs.diMN 00072034A01 ctrl ctrl 7 87856433
neurolincs.diMN 00072028B01 ctrl ctrl 5 84686602
neurolincs.diMN 00072028A01 ctrl ctrl 6 86183708
neurolincs.diMN 00072010B02 ctrl ctrl 10 71171884
neurolincs.diMN 00072010A02 ctrl ctrl 7 72849067
neurolincs.diMN 00072002B02 ctrl ctrl 8 81893396
neurolincs.diMN 00072002A02 ctrl ctrl 8 78862140
neurolincs.diMN 00072007B01 als sporadic 14 95655968
neurolincs.diMN 00072007A01 als sporadic 16 86353118
neurolincs.diMN 00072006B01 als sporadic 8 88663514
neurolincs.diMN 00072006A01 als sporadic 8 87562150
neurolincs.diMN 00072019B02 als sporadic 5 102600997
neurolincs.diMN 00072019A02 als sporadic 4 81561535
neurolincs.diMN 00072001B02 als sporadic 11 68658150
neurolincs.diMN 00072001A02 als sporadic 5 92152108
neurolincs.diMN 00072029B01 als sod1 9 88644882
neurolincs.diMN 00072029A01 als sod1 9 69660338
neurolincs.diMN 00072018B02 als sod1 6 92304897
neurolincs.diMN 00072018A02 als sod1 5 78852703
neurolincs.diMN 00072008B02 als sod1 4 93585462
neurolincs.diMN 00072008A02 als sod1 6 80849799
neurolincs.diMN 00072015B01 als c9orf72 5 81357232
neurolincs.diMN 00072015A01 als c9orf72 8 80643118
neurolincs.diMN 00072012B01 als c9orf72 9 77973353
neurolincs.diMN 00072012A01 als c9orf72 9 96935001
neurolincs.diMN 00072014B02 als c9orf72 7 92196364
neurolincs.diMN 00072014A02 als c9orf72 3 83893881
neurolincs.diMN 00072013B02 als c9orf72 8 35176115
neurolincs.diMN 00072013A02 als c9orf72 6 77127001
neurolincs.iMN A-042-52iALS-004 als c9orf72 4 70623351
neurolincs.iMN A-042-52iALS-003 als c9orf72 3 54474248
neurolincs.iMN A-042-30iALS-004 als c9orf72 3 82501857
neurolincs.iMN A-042-30iALS-003 als c9orf72 3 62344831
neurolincs.iMN A-042-29iALS-004 als c9orf72 3 71722128
neurolincs.iMN A-042-29iALS-003 als c9orf72 4 67369943
neurolincs.iMN A-042-28iALS-005 als c9orf72 9 67180410
neurolincs.iMN A-042-28iALS-003 als c9orf72 8 50323795
neurolincs.iMN A-042-83iCTR-004 ctrl ctrl 6 59263773
neurolincs.iMN A-042-83iCTR-003 ctrl ctrl 4 59709899
neurolincs.iMN A-042-25iCTR-004 ctrl ctrl 8 79504132
neurolincs.iMN A-042-25iCTR-003 ctrl ctrl 7 61589963
neurolincs.iMN A-042-00iCTR-004 ctrl ctrl 4 64065133
neurolincs.iMN A-042-00iCTR-003 ctrl ctrl 3 58621934
catanese c9orf72_6 als c9orf72 12 44556823
catanese c9orf72_5 als c9orf72 18 44718862
catanese c9orf72_4 als c9orf72 16 48198617
catanese c9orf72_3 als c9orf72 11 49885755
catanese c9orf72_2 als c9orf72 9 50374657
catanese c9orf72_1 als c9orf72 12 52025076
catanese ctrl_3 ctrl ctrl 4 41908415
catanese ctrl_2 ctrl ctrl 8 41297925
catanese ctrl_1 ctrl ctrl 10 43538558
catanese fus_6 als fus 3 43123381
catanese fus_5 als fus 5 43486913
catanese fus_4 als fus 7 40817402
catanese fus_3 als fus 10 47197324
catanese fus_2 als fus 7 43048688
catanese fus_1 als fus 11 45844283
catanese iso_3 ctrl iso 9 48361792
catanese iso_2 ctrl iso 9 47178499
catanese iso_1 ctrl iso 6 44076352
dafinca.c9orf72 c9orf72_4 als c9orf72 3 42732664
dafinca.c9orf72 c9orf72_3 als c9orf72 3 41062026
dafinca.c9orf72 c9orf72_2 als c9orf72 2 48882465
dafinca.c9orf72 c9orf72_1 als c9orf72 3 46262015
dafinca.c9orf72 ctrl_1 ctrl ctrl 5 45099717
dafinca.c9orf72 iso_7 ctrl iso 1 36358941
dafinca.c9orf72 iso_6 ctrl iso 2 36968802
dafinca.c9orf72 iso_5 ctrl iso 1 39174051
dafinca.c9orf72 iso_4 ctrl iso 4 35084625
dafinca.c9orf72 iso_3 ctrl iso 4 45037650
dafinca.c9orf72 iso_2 ctrl iso 4 41434677
dafinca.c9orf72 iso_1 ctrl iso 2 43145131
dafinca.tardbp ctrl_4 ctrl ctrl 5 13922252
dafinca.tardbp ctrl_3 ctrl ctrl 11 18207019
dafinca.tardbp ctrl_2 ctrl ctrl 5 17409430
dafinca.tardbp ctrl_1 ctrl ctrl 7 15358338
dafinca.tardbp tardbp_6 als tardbp 3 18450547
dafinca.tardbp tardbp_5 als tardbp 6 16996133
dafinca.tardbp tardbp_4 als tardbp 5 17702995
dafinca.tardbp tardbp_3 als tardbp 5 18246091
dafinca.tardbp tardbp_2 als tardbp 8 16856043
dafinca.tardbp tardbp_1 als tardbp 5 17886729
wang iso_2 ctrl iso 9 25470901
wang iso_1 ctrl iso 16 25318736
wang sod1_2 als sod1 18 25959947
wang sod1_1 als sod1 14 26086164
kiskinis iso_3 ctrl iso 12 14683349
kiskinis iso_2 ctrl iso 9 9190834
kiskinis iso_1 ctrl iso 7 10724700
kiskinis sod1_2 als sod1 38 13383139
kiskinis sod1_1 als sod1 28 7037516
sommer c9orf72_1 als c9orf72 3 40465430
sommer c9orf72_2 als c9orf72 4 38631160
sommer c9orf72_3 als c9orf72 4 41347502
sommer c9orf72_4 als c9orf72 2 50500461
sommer c9orf72_5 als c9orf72 3 40439998
sommer c9orf72_6 als c9orf72 3 46224895
sommer ctrl_1 ctrl ctrl 2 41738904
sommer ctrl_2 ctrl ctrl 5 46986721
sommer ctrl_3 ctrl ctrl 7 43178218
sommer ctrl_4 ctrl ctrl 3 39573053
sommer ctrl_5 ctrl ctrl 4 40502175
sommer ctrl_6 ctrl ctrl 4 36822732
desantis ctrl_3 ctrl ctrl 5 29102751
desantis ctrl_2 ctrl ctrl 2 18402574
desantis ctrl_1 ctrl ctrl 8 27289409
desantis fus_3 als fus 9 26858355
desantis fus_2 als fus 2 16997472
desantis fus_1 als fus 8 24909519
smith tardbp_3 als tardbp 1 7448645
smith tardbp_2 als tardbp 1 7455838
smith ctrl_2 ctrl ctrl 1 7445173
smith tardbp_1 als tardbp 0 7471156
smith ctrl_1 ctrl ctrl 0 7248337

Table S10 RNA fusion burden

ipsc_mn_als_datasets.starfusion.als.count = ipsc_mn_als_datasets.starfusion %>% filter(condition == "als") %>% count(breakpoints, name = "als_yes")
ipsc_mn_als_datasets.starfusion.ctrl.count = ipsc_mn_als_datasets.starfusion %>% filter(condition == "ctrl") %>% count(breakpoints, name = "ctrl_yes")
ipsc_mn_als_datasets.starfusion.als_ctrl.prop = ipsc_mn_als_datasets.starfusion.als.count %>% full_join(ipsc_mn_als_datasets.starfusion.ctrl.count)  %>% replace(is.na(.),0) %>% 
  mutate(als_total = 360, ctrl_total = 90) 
ipsc_mn_als_datasets.starfusion.als_ctrl.burden = ipsc_mn_als_datasets.starfusion.als_ctrl.prop %>% rowwise() %>% 
  mutate(p_value = ClusterBurden::burden_test(n1 = als_yes, n2 = ctrl_yes, ss1 = als_total, ss2 = ctrl_total), 
         odds_ratio = ClusterBurden::burden_test(n1 = als_yes, n2 = ctrl_yes, ss1 = als_total, ss2 = ctrl_total, pval = FALSE)$estimate[1],
         lower_ci = ClusterBurden::burden_test(n1 = als_yes, n2 = ctrl_yes, ss1 = als_total, ss2 = ctrl_total, pval = FALSE)$conf.int[1], 
         upper_ci = ClusterBurden::burden_test(n1 = als_yes, n2 = ctrl_yes, ss1 = als_total, ss2 = ctrl_total, pval = FALSE)$conf.int[2])
als_ctrl.voila = read_voila_het(here(proj_path,"splicing/majiq_polyA/voila-tsv/als_vs_ctrl.tsv"), grp1 = "als", grp2 = "ctrl")
als_ctrl.voila.splicing_genes = als_ctrl.voila %>% filter(changing_dpsi0.1 == TRUE) %>% distinct(gene_name) %>% pull(gene_name)
ipsc_mn_als_datasets.starfusion.als_ctrl.burden_table = ipsc_mn_als_datasets.starfusion.als_ctrl.burden %>% left_join(distinct(select(ipsc_mn_als_datasets.starfusion, breakpoints, fusion_name, fusion_type))) %>% arrange(p_value) %>% 
  mutate(gene1 = str_split_fixed(fusion_name, "--",2)[,1], gene2 = str_split_fixed(fusion_name, "--",2)[,2], alterated_splicing = case_when(gene1 %in% als_ctrl.voila.splicing_genes | gene2 %in% als_ctrl.voila.splicing_genes ~ "yes", TRUE ~ "")) %>%
  select(fusion_name, breakpoints, fusion_type, als_number = als_yes, ctrl_number = ctrl_yes, odds_ratio, lower_ci, upper_ci, p_value, alterated_splicing)
kbl(ipsc_mn_als_datasets.starfusion.als_ctrl.burden_table) %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), fixed_thead = T) %>% scroll_box(width = "100%", height = "500px")
fusion_name breakpoints fusion_type als_number ctrl_number odds_ratio lower_ci upper_ci p_value alterated_splicing
LINC01572–PMFBP1 16:72284572:-_16:72164916:- Neighbours 78 7 3.2728937 1.6047187 Inf 0.0011203
Z68871.1–LINC00630 X:102905737:+_X:102839801:+ Overlapping Neighbours 181 29 2.1234663 1.3759543 Inf 0.0014416
AC010332.1–ZNF880 19:52392788:+_19:52373111:+ Local Rearrangement 200 35 1.9613446 1.2874724 Inf 0.0032937
KRTAP5-AS1–AP000867.5 11:1598289:+_11:71563684:- Distant Proximity 121 18 2.0221779 1.2305056 Inf 0.0075401
C15orf40–HOMER2 15:83010237:-_15:82892841:- Neighbours 17 0 Inf 1.3333228 Inf 0.0208346
CAVIN4–TMEFF1 9:100585927:+_9:100498765:+ Local Rearrangement 165 30 1.6903608 1.0980652 Inf 0.0208959
CAVIN4–MSANTD3-TMEFF1 9:100585927:+_9:100498765:+ Local Rearrangement 165 30 1.6903608 1.0980652 Inf 0.0208959
LARS2–LIMD1 3:45524108:+_3:45636150:+ Neighbours 94 15 1.7648808 1.0352138 Inf 0.0385663
SPRY4-AS1–LINC01844 5:142581914:+_5:142745208:+ Neighbours 21 1 5.5008163 1.0360787 Inf 0.0441840
NREP–HMGN1P13 5:111735430:-_5:111572325:- Neighbours 53 8 1.7675789 0.8839976 Inf 0.0979401
CRYBB2P1–GRK3 22:25520733:+_22:25604377:+ Neighbours 10 0 Inf 0.7222905 Inf 0.1046809
CRYBB2P1–GRK3 22:25459515:+_22:25604377:+ Neighbours 32 4 2.0948470 0.8181814 Inf 0.1166954
PTCHD4–AL353138.1 6:48008634:-_6:48069926:- Local Rearrangement 41 6 1.7974036 0.8173929 Inf 0.1297229
CRIPT–SOCS5 2:46619681:+_2:46758519:+ Neighbours 9 0 Inf 0.6372242 Inf 0.1315222
SUB1–NPR3 5:32591685:+_5:32724698:+ Neighbours 14 1 3.5943007 0.6480436 Inf 0.1624562
NKAPP1–RHOXF1 X:120244764:-_X:120112914:- Neighbours 8 0 Inf 0.5528235 Inf 0.1651500
ZNF350-AS1–ZNF613 19:51949235:+_19:51948593:+ Local Rearrangement 108 22 1.3238770 0.8260146 Inf 0.1819186
PHOSPHO2–SSB 2:169697531:+_2:169800952:+ Neighbours 28 4 1.8111304 0.6999659 Inf 0.1945447
KLHL23–SSB 2:169697531:+_2:169800952:+ Neighbours 28 4 1.8111304 0.6999659 Inf 0.1945447
AC119396.2–INSR 19:7390576:-_19:7267896:- Neighbours 31 5 1.6002867 0.6737518 Inf 0.2356393
LINC01572–PMFBP1 16:72284577:-_16:72164916:- Neighbours 16 2 2.0438043 0.5539893 Inf 0.2658738
AL035409.2–ST6GALNAC5 1:77068843:+_1:77044204:+ Local Rearrangement 34 6 1.4589710 0.6548855 Inf 0.2747451
USP22–RN7SL5P 17:21000941:-_9:9442093:+ Inter Chromosomal 29 5 1.4882051 0.6230567 Inf 0.2903729
CCDC122–ENOX1 13:43874842:-_13:43667544:- Neighbours 84 18 1.2169099 0.7323742 Inf 0.3003889
CXXC5–PSD2 5:139648845:+_5:139809391:+ Distant Proximity 15 2 1.9107102 0.5134713 Inf 0.3047402
DR1–FNBP1L 1:93354071:+_1:93499468:+ Neighbours 10 1 2.5389621 0.4341852 Inf 0.3188009
AC068446.2–NBEAP1 15:21298706:-_15:20671268:- Distant Proximity 5 0 Inf 0.3042365 Inf 0.3258509
AC068446.2–AC060814.4 15:21324988:-_15:21328980:- Local Rearrangement 5 0 Inf 0.3042365 Inf 0.3258509
CAVIN4–MSANTD3-TMEFF1 9:100578551:+_9:100498765:+ Local Rearrangement 5 0 Inf 0.3042365 Inf 0.3258509
CAVIN4–TMEFF1 9:100578551:+_9:100498765:+ Local Rearrangement 5 0 Inf 0.3042365 Inf 0.3258509
SEPTIN7P2–PSPH 7:45768660:-_7:56021231:- Distant Proximity 19 3 1.6142971 0.5366688 Inf 0.3262606
PSPC1–ZMYM5 13:19730239:-_13:19835689:- Local Rearrangement 52 11 1.2120054 0.6523621 Inf 0.3625712
YAF2–RYBP 12:42238155:-_3:72446621:- Inter Chromosomal 9 1 2.2788627 0.3817097 Inf 0.3730935
C1QTNF3-AMACR–AC138409.2 5:34124418:-_5:34182867:- Local Rearrangement 9 1 2.2788627 0.3817097 Inf 0.3730935
LINC01145–SRGAP2B 1:145215639:-_1:145093443:- Neighbours 13 2 1.6468051 0.4332582 Inf 0.3946244
CRYBB2P1–GRK3 22:25520733:+_22:25644592:+ Neighbours 17 3 1.4362559 0.4709196 Inf 0.4074672
FNBP1L–MTF2 1:93448305:+_1:93110230:+ Distant Proximity 4 0 Inf 0.2236690 Inf 0.4082290
MFNG–ELFN2 22:37476896:-_22:37375996:- Neighbours 4 0 Inf 0.2236690 Inf 0.4082290
RARB–AC092422.1 3:25174575:+_3:25060125:+ Local Rearrangement 4 0 Inf 0.2236690 Inf 0.4082290
PCMTD1–PXDNL 8:51898930:-_8:51654760:- Neighbours 4 0 Inf 0.2236690 Inf 0.4082290
LINC01933–AC008571.2 5:152267355:+_5:152537704:+ Distant Proximity 8 1 2.0201305 0.3296629 Inf 0.4341726
NREP–HMGN1P13 5:111677940:-_5:111572325:- Neighbours 28 6 1.1803022 0.5211467 Inf 0.4620774
AC012414.4–AC012414.2 15:20755930:-_15:20761158:- Local Rearrangement 11 2 1.3858939 0.3542338 Inf 0.4999902
MFSD14B–AL691447.2 9:94438528:+_9:94338836:+ Local Rearrangement 7 1 1.7629706 0.2781994 Inf 0.5019998
AC092745.5–AC092745.2 12:8251507:+_12:8368982:+ Overlapping Neighbours 3 0 Inf 0.1453421 Inf 0.5111438
PSPC1–ZMYM5 13:19741565:-_13:19835689:- Local Rearrangement 3 0 Inf 0.1453421 Inf 0.5111438
LINC00674–AMZ2 17:68114525:+_17:68250188:+ Neighbours 3 0 Inf 0.1453421 Inf 0.5111438
AC022140.1–AC099499.1 5:25445820:-_5:25298609:- Distant Proximity 3 0 Inf 0.1453421 Inf 0.5111438
MRPL14–AL109615.3 6:44114077:-_6:44001116:- Neighbours 3 0 Inf 0.1453421 Inf 0.5111438
KIAA1958–SNX30 9:112575251:+_9:112804776:+ Neighbours 3 0 Inf 0.1453421 Inf 0.5111438
TMEM164–RTL9 X:110171520:+_X:110445153:+ Distant Proximity 3 0 Inf 0.1453421 Inf 0.5111438
AL353138.1–PTCHD4 6:48111049:-_6:48009114:- Neighbours 293 73 1.0183603 0.5851179 Inf 0.5285463
LINC01315–TCF20 22:42368715:-_22:42215341:- Neighbours 34 8 1.0688608 0.5190433 Inf 0.5294393
PRDM2–KAZN 1:13843107:+_1:14180435:+ Neighbours 18 4 1.1312776 0.4170870 Inf 0.5418132
BBOX1-AS1–SLC5A12 11:27151050:-_11:26712706:- Distant Proximity 14 3 1.1730102 0.3739383 Inf 0.5479357
AC022523.1–LINC00923 15:98046667:-_15:97758661:- Distant Proximity 14 3 1.1730102 0.3739383 Inf 0.5479357
AC007318.1–RAB1A 2:65227485:-_2:65104806:- Neighbours 6 1 1.5072445 0.2273381 Inf 0.5761020
SHROOM2–WWC3 X:9944913:+_X:10063445:+ Neighbours 17 4 1.0654241 0.3897934 Inf 0.5860321
USP22–RN7SL2 17:21000941:-_14:49862816:- Inter Chromosomal 36 9 1.0000000 0.5019715 Inf 0.5896286
USP22–AL627171.2 17:21000941:-_14:49862816:- Inter Chromosomal 36 9 1.0000000 0.5019715 Inf 0.5896286
AC096642.2–LYPLAL1 1:219295151:+_1:219193082:+ Local Rearrangement 2 0 Inf 0.0718293 Inf 0.6396437
MIR3659HG–AL390839.2 1:38047614:+_1:38209271:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
SLIRP–ADCK1 14:77715879:+_14:77818968:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
ADAMTSL3–SH3GL3 15:83704508:+_15:83559253:+ Local Rearrangement 2 0 Inf 0.0718293 Inf 0.6396437
AC110023.1–AC091078.1 15:93592733:+_15:93553605:+ Local Rearrangement 2 0 Inf 0.0718293 Inf 0.6396437
LINC01572–PMFBP1 16:72284577:-_16:72171268:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
LINC01572–PMFBP1 16:72284577:-_16:72174070:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
CDH13–HSBP1 16:83486655:+_16:83808680:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
USP22–RN7SL4P 17:21000941:-_3:15738548:+ Inter Chromosomal 2 0 Inf 0.0718293 Inf 0.6396437
ARL17B–KANSL1 17:46352820:-_17:46094701:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
SNHG16–METTL23 17:76614005:+_17:76732978:+ Distant Proximity 2 0 Inf 0.0718293 Inf 0.6396437
SNHG16–AC005837.2 17:76614005:+_17:76732978:+ Distant Proximity 2 0 Inf 0.0718293 Inf 0.6396437
RNF138–MEP1B 18:32092886:+_18:32204182:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
MYDGF–SEMA6B 19:4659931:-_19:4558489:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
AC007318.1–RAB1A 2:65227428:-_2:65104806:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
RNF144A–AC013460.1 2:7075684:+_2:7421184:+ Distant Proximity 2 0 Inf 0.0718293 Inf 0.6396437
MBOAT2–KIDINS220 2:9003540:-_2:8827129:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
CHMP4B–DEFB115 20:33811658:+_20:31249509:+ Distant Proximity 2 0 Inf 0.0718293 Inf 0.6396437
C20orf194–PIAS1 20:3407475:-_15:68086306:+ Inter Chromosomal 2 0 Inf 0.0718293 Inf 0.6396437
PPM1F–MAPK1 22:21931148:-_22:21807846:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
CRYBB2P1–GRK3 22:25520733:+_22:25667739:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
SYN3–RTCB 22:32596674:-_22:32408833:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
AC068756.1–AC108690.1 3:80761438:-_3:80633971:- Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
AC026410.3–RAPGEF1 5:80351234:-_9:131650949:- Inter Chromosomal 2 0 Inf 0.0718293 Inf 0.6396437 yes
MAILR–ATP6V1C1 8:102880058:+_8:103040798:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
LINC00032–EQTN 9:27277551:-_9:27286362:- Overlapping Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
ERMP1–KIAA2026 9:5787061:-_9:5914062:- Local Rearrangement 2 0 Inf 0.0718293 Inf 0.6396437
BHLHB9–LINC00630 X:102721027:+_X:102826969:+ Neighbours 2 0 Inf 0.0718293 Inf 0.6396437
PFKFB3–LINC02649 10:6226365:+_10:6326546:+ Neighbours 23 6 0.9555832 0.4134739 Inf 0.6453096
BTF3L4–ZFYVE9 1:52064938:+_1:52216369:+ Neighbours 5 1 1.2529300 0.1772958 Inf 0.6553631
EFL1P1–AC243562.2 15:84126600:+_15:84389732:+ Distant Proximity 5 1 1.2529300 0.1772958 Inf 0.6553631
LINC01572–PMFBP1 16:72284572:-_16:72171268:- Neighbours 5 1 1.2529300 0.1772958 Inf 0.6553631
TIAM2–SCAF8 6:154944206:+_6:154773989:+ Overlapping Neighbours 5 1 1.2529300 0.1772958 Inf 0.6553631
AC009315.1–FSIP2 2:185434191:+_2:185739346:+ Distant Proximity 19 5 0.9473240 0.3790265 Inf 0.6580759
AC010332.1–ZNF880 19:52392776:+_19:52315951:+ Local Rearrangement 8 2 1.0000000 0.2381207 Inf 0.6784890
BHLHB9–LINC00630 X:102721091:+_X:102826969:+ Neighbours 8 2 1.0000000 0.2381207 Inf 0.6784890
LINC01145–SRGAP2 1:145215639:-_1:206205429:+ Distant Proximity 11 3 0.9142135 0.2790496 Inf 0.6997665
AC068446.2–AC060814.4 15:21324988:-_15:21330231:- Local Rearrangement 4 1 1.0000000 0.1284236 Inf 0.7377411
LINC01572–PMFBP1 16:72249163:-_16:72164916:- Neighbours 4 1 1.0000000 0.1284236 Inf 0.7377411
RPL37A–AC073321.1 2:216500031:+_2:216610744:+ Neighbours 4 1 1.0000000 0.1284236 Inf 0.7377411
MED27–RAPGEF1 9:131884058:-_9:131650949:- Distant Proximity 4 1 1.0000000 0.1284236 Inf 0.7377411 yes
AL355987.4–GPI 9:136802786:+_19:34393248:+ Inter Chromosomal 34 10 0.8346905 0.4270443 Inf 0.7554429
CCDC183–GPI 9:136802786:+_19:34393248:+ Inter Chromosomal 34 10 0.8346905 0.4270443 Inf 0.7554429
AL355987.2–GPI 9:136802786:+_19:34393248:+ Inter Chromosomal 34 10 0.8346905 0.4270443 Inf 0.7554429
AEBP2–AC024901.1 12:19720691:+_12:19923198:+ Neighbours 9 3 0.7441212 0.2171197 Inf 0.7969835
PTS–LINC02762 11:112237506:+_11:112360069:+ Neighbours 6 2 0.7462908 0.1628979 Inf 0.7984087
AC009315.1–FSIP2 2:185502739:+_2:185739346:+ Distant Proximity 6 2 0.7462908 0.1628979 Inf 0.7984087
SLC16A1-AS1–LRIG2 1:112960575:+_1:113091318:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
MIIP–MFN2 1:12022917:+_1:12014257:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
LINC01138–FCGR1CP 1:148459602:-_1:143880437:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
RABGAP1L–MED14 1:174278779:+_X:40729345:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CEP350–TDRD5 1:179987286:+_1:179690696:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
CNIH3–WDR26 1:224434862:+_1:224431781:- Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AKT3–RPS10 1:243504348:-_6:34426060:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AKT3–RPS10 1:243504388:-_6:34426060:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
GMEB1–SMG1 1:28683740:+_16:18896956:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZFP69B–LIFR 1:40457071:+_5:38511964:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PLK3–RPS8 1:44802855:+_1:44778000:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
BTF3L4–ZFYVE9 1:52064938:+_1:52199251:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AL669831.3–DCX 1:631066:-_X:111299018:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
INPP5F–NOVA1 10:119823199:+_14:26448963:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
BX322639.1–CCNYL2 10:42360949:-_10:42433354:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
BX322639.1–CCNYL2 10:42367816:-_10:42433354:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
AGAP4–PARGP1 10:45841653:-_10:45964871:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
MRPS16–CFAP70 10:73251763:-_10:73256416:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
GLUD1P3–LMBR1 10:73730873:+_7:156826744:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
POLR3A–HMGCS1 10:78002197:-_5:43297166:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NUTM2B-AS1–SFTPA2 10:79766271:-_10:79559506:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
NRG3–KRTAP5-AS1 10:81876163:+_11:1597248:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NUTM2A-AS1–GLUD1 10:87326630:-_10:87076656:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
NKAPD1–CPSF3 11:112075643:+_2:9441818:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZBTB16–NXPE2 11:114187038:+_11:114679657:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
JAM3–PTPN11 11:134069159:+_12:112446276:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
DNAJC24–IMMP1L 11:31370859:+_11:31433570:- Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
PTDSS2–DLGAP4 11:448419:+_20:36525851:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PHF21A–SPCS2 11:46076754:-_11:74965034:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
PTDSS2–DAZAP1 11:479152:+_19:1417500:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
MALAT1–ADGRV1 11:65505019:+_5:90720935:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PACS1–UQCC2 11:66210451:+_6:33700513:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
RBM14–C11orf80 11:66617057:+_11:66759043:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000 yes
UBE3B–MYCN 12:109526416:+_2:15945493:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CFAP73–TSPAN4 12:113152887:+_11:847201:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NCOR2–AC048337.1 12:124362126:-_12:121391970:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000 yes
NCOR2–RNF34 12:124362126:-_12:121416159:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000 yes
AEBP2–AC024901.1 12:19518113:+_12:19923198:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
BICD1–FGD4 12:32107544:+_12:32564137:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
TUBA1A–PTMS 12:49185036:-_12:6770157:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
TUBA1A–NEFM 12:49185049:-_8:24917437:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CPSF6–JAG2 12:69262562:+_14:105141329:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CPSF6–ADGRB3 12:69262562:+_6:69372406:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CPSF6–KBTBD11 12:69262562:+_8:2006545:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TBC1D15–RAB21 12:71885021:+_12:71782031:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
PPP1R12A–CAPS2-AS1 12:79817394:-_12:75250493:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
ATP2B1–PCSK2 12:89627678:-_20:17436708:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PSPC1–ZMYM5 13:19772242:-_13:19835689:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
PSPC1–ZMYM5 13:19782386:-_13:19852190:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
PSPC1–ZMYM5 13:19782386:-_13:19862466:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
TPTE2P5–MRPS31 13:40908159:-_13:40767033:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
VWA8–SH3YL1 13:41865736:-_2:230044:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
FARP1–IPO5 13:98213413:+_13:98006130:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
SLC38A6–PRKCH 14:61030523:+_14:61391225:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC012414.4–IGHV1OR15-6 15:20755930:-_15:20639759:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AC012414.4–AC100757.2 15:20755930:-_15:22360628:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC124312.1–ATP2B1 15:24982437:+_12:89656107:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TTBK2–SMG1P3 15:42827928:-_16:21487616:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AC012405.1–AC073941.1 15:46410353:+_15:46791282:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
MIR4713HG–GLDN 15:51037681:+_15:51377449:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
MIR4713HG–GLDN 15:51037681:+_15:51383785:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
TLN2–TLN1 15:62833629:+_9:35698679:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
UBE2Q2P2–AC243562.1 15:82355374:+_15:84394809:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
C15orf40–HOMER2 15:83008548:-_15:82892841:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
IGF1R–LUNAR1 15:98708107:+_15:99024600:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
IGF1R–SYNM 15:98708107:+_15:99113591:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
PDXDC1–NOMO1 16:15030056:+_16:14838407:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
PKD1P6–MAZ 16:15133264:-_16:29808230:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
UQCRC2–PJA2 16:21976243:+_5:109356026:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
DNASE1–PTBP1 16:3612006:+_19:799413:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
UTP4–SNTB2 16:69143389:+_16:69245602:+ Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
ANKRD11–CAMK2B 16:89418284:-_7:44263064:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000 yes
DEF8–OSGEP 16:89949513:+_14:20449301:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000 yes
C16orf72–AC012178.1 16:9103259:+_16:9461042:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
SUZ12P1–AC005562.1 17:30709811:+_17:30631755:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000 yes
AC138207.8–NF1 17:31045549:+_17:31155983:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
ARL17A–KANSL1 17:46570759:-_17:46094701:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
NPEPPS–TBC1D3I 17:47592545:+_17:36262986:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
SPOP–MSI2 17:49677933:-_17:57401379:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
GDPD1–GIT2 17:59272836:+_12:109961685:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TANC2–PSMA3 17:63319090:+_14:58247750:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
VPS53–GLOD4 17:710533:-_17:785977:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
ATP1B2–AL627171.2 17:7656775:+_14:49862816:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
FAAP100–TRIOBP 17:81544004:-_22:37733298:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TBCD–ATP8B3 17:82911789:+_19:1800449:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NTN1–AL121594.1 17:9221242:+_14:35266727:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
DOK6–AC006305.1 18:69599498:+_18:56181474:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC124254.2–AC123786.1 18:77422024:+_18:77613183:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
EIF3G–ENO4 19:10118668:-_10:116862799:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TCF3–CCDC57 19:1646355:-_17:82101866:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZNF493–CRCP 19:21397267:+_7:66127704:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AC092279.1–RBM39 19:24049014:+_20:35725155:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NFIC–CTBP1 19:3359685:+_4:1241519:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZBTB7A–WDR59 19:4053971:-_16:74956610:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZNF175–SRP68 19:51581882:+_17:76040474:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZNF846–ZNF561-AS1 19:9785938:-_19:9627716:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000 yes
KLHL23–SSB 2:169695247:+_2:169800952:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AC074286.1–AC092162.2 2:177094575:-_2:176812193:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC021851.1–NUP35 2:183182680:+_2:183151508:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
AC009315.1–FSIP2 2:185434187:+_2:185737013:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC009315.1–FSIP2 2:185502739:+_2:185737013:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC097500.1–LINC01473 2:185950644:-_2:186086370:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
WDR75–KLF7 2:189441578:+_2:207124404:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
PUM2–SMAD5 2:20327310:-_5:136160856:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
MAPRE3–ACYP2 2:26970802:+_2:54135453:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
LTBP1–BIRC6 2:33021206:+_2:32406499:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
CRIPT–SOCS5 2:46648138:+_2:46758519:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
SPTBN1–RTN4 2:54558887:+_2:54987698:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC007318.1–RAB1A 2:65227481:-_2:65104806:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
RNF144A–AC013460.1 2:6997061:+_2:7421184:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AL050403.2–PLXDC2 20:10673025:+_10:20211669:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PTPRA–ATF2 20:2965202:+_2:175151158:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
FASTKD5–CARS2 20:3159766:-_13:110701555:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
TTI1–VSTM2L 20:37996375:-_20:37931635:+ Local Inversion 1 0 Inf 0.0131578 Inf 0.8000000
SULF2–CKS1B 20:47736703:-_1:154978725:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
VAPB–APCDD1L-DT 20:58418363:+_20:58547812:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
CDH4–ERICH1 20:61254937:+_8:674047:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
VPS26C–TTC3 21:37267238:-_21:37108392:+ Local Inversion 1 0 Inf 0.0131578 Inf 0.8000000
GUSBP11–AC113385.3 22:23659865:-_5:100381398:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CRYBB2P1–GRK3 22:25459515:+_22:25661576:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
GALR3–ANKRD54 22:37823765:+_22:37838593:- Local Inversion 1 0 Inf 0.0131578 Inf 0.8000000
RAB43–GORASP2 3:129121286:-_2:170948350:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
LINC02021–COL6A4P2 3:130112744:+_3:130212823:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
ANAPC13–AMOTL2 3:134482806:-_3:134371494:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC046134.2–CLSTN2 3:139583880:+_3:140175951:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
TFDP2–XRN1 3:142101735:-_3:142365366:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
METTL6–SH3BP5 3:15415772:-_3:15304231:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
EGFEM1P–KANSL1L 3:168824925:+_2:210154611:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
SLC7A14-AS1–AC061708.1 3:170708194:+_3:170994873:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
ERC2–CDC42BPA 3:56007181:-_1:227048010:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
UBA3–STRAP 3:69077798:-_12:15890597:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
ZNF717–RPL23AP49 3:75741276:-_3:75625153:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AC068756.1–AC108690.1 3:80761458:-_3:80633971:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
LINC02050–LINC02027 3:80770955:+_3:81095112:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC107029.2–COL8A1 3:99635662:+_3:99744897:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AC108865.1–AC110772.2 4:186891368:+_4:187019821:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
PCDH7–LINC02497 4:30920369:+_4:31176621:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
CFAP299–BMP3 4:80870135:+_4:81045738:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
EPB41L4A–NREP 5:112168739:-_5:111735507:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AP3S1–LVRN 5:115870128:+_5:115983287:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
LYRM7–CDC42SE2 5:131171038:+_5:131315976:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
UIMC1–UBE2B 5:177022464:-_5:134390225:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
C1QTNF3-AMACR–AC138409.2 5:34020587:-_5:34182867:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
TTC33–PRKAA1 5:40728345:-_5:40777586:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
RTN4IP1–LINC02532 6:106583328:-_6:106718242:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
CEP57L1–AFG1L 6:109095575:+_6:108519697:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
CEP57L1–TTC6 6:109146937:+_14:37807320:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
NEDD9–AC018630.4 6:11232504:-_12:11047188:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
RNF217–TPD52L1 6:125045444:+_6:125220078:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AL133346.1–AL021408.1 6:131951254:+_6:132098931:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
TBPL1–AHI1 6:133953425:+_6:135290525:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
CCDC170–TBC1D32 6:151615679:+_6:121239188:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
ATXN1–ZFYVE27 6:16753233:-_10:97744729:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AL662797.1–TUBA1A 6:30723725:-_12:49185063:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
RNF5–TSBP1-AS1 6:32180126:+_6:32365780:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AL021368.4–UBE4B 6:57959028:-_1:10161142:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
KHDRBS2-OT1–KHDRBS2 6:61652255:-_6:61707403:- Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
EEF1A1–RPS11 6:73519337:-_19:49497194:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AL391840.3–SH3BGRL2 6:79631633:+_6:79673614:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
EEF1E1-BLOC1S5–SMIM13 6:8097267:-_6:11134403:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
CNPY4–RPS6KC1 7:100119862:+_1:213242569:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
FAM185A–LRRC17 7:102808351:+_7:102933774:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
FBXL13–AC105052.5 7:102822040:-_7:102703527:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
RINT1–AC073073.1 7:105548710:+_7:105530509:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
MTPN–CHRM2 7:135977029:-_7:137014820:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
IQCE–SH3RF1 7:2573488:+_4:169156679:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
HOTAIRM1–WDR75 7:27096388:+_2:189458753:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
OGDH–ZNF816-ZNF321P 7:44681848:+_19:52929414:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AC079781.5–BBS2 7:97854580:-_16:56485738:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
BUD31–PDAP1 7:99410169:+_7:99400424:- Local Inversion 1 0 Inf 0.0131578 Inf 0.8000000
DLC1–TPTEP2 8:13604537:-_22:38336706:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AC138696.1–MOB3A 8:143251340:+_19:2078679:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AC138696.1–ELFN1 8:143251340:+_7:1709091:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PLEC–PARP10 8:143975177:-_8:143986438:- Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000 yes
HGH1–CPSF6 8:144137958:+_12:69239612:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
RB1CC1–AMN1 8:52645702:-_12:31672377:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
CAVIN4–MSANTD3-TMEFF1 9:100578551:+_9:100576516:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
CAVIN4–MSANTD3-TMEFF1 9:100586185:+_9:100498765:+ Local Rearrangement 1 0 Inf 0.0131578 Inf 0.8000000
PTGR1–CHD9 9:111592926:-_16:53235185:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000 yes
KIAA1958–SNX30 9:112487118:+_9:112804776:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
INIP–C9orf147 9:112717987:-_9:112487090:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
ZBTB34–RALGPS1 9:126860739:+_9:126962225:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
PRRC2B–ATP5PO 9:131432794:+_21:33904021:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
PRRC2B–ANP32B 9:131439061:+_9:98015364:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
MED27–RAPGEF1 9:131853035:-_9:131650949:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000 yes
AL355987.4–MAN1B1 9:136808326:+_9:137088075:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
LINC00032–EQTN 9:27271927:-_9:27286362:- Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
LINC00032–EQTN 9:27274090:-_9:27286362:- Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
OSTF1–APP 9:75088726:+_21:26112146:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
MT-CO3–AL450405.1 MT:9411:+_6:117998990:+ Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
Z68871.1–LINC00630 X:102905737:+_X:102816992:+ Overlapping Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
TMEM164–RTL9 X:110173453:+_X:110445153:+ Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC073529.1–MID1 X:11038603:-_X:10567603:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
AC073529.1–MID1 X:11106901:-_X:10567603:- Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
DDX3X–STK39 X:41337465:+_2:167964726:- Inter Chromosomal 1 0 Inf 0.0131578 Inf 0.8000000
AL050309.1–KLF8 X:55908800:+_X:56250231:+ Neighbours 1 0 Inf 0.0131578 Inf 0.8000000
NLGN4X–AC110995.1 X:5844434:-_X:5669606:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
PNPLA4–ANOS1 X:7912028:-_X:8623670:- Distant Proximity 1 0 Inf 0.0131578 Inf 0.8000000
AC074286.1–AC073636.1 2:177094575:-_2:176846377:- Distant Proximity 15 5 0.7396686 0.2857924 Inf 0.8087205
SPSB4–PXYLP1 3:141066798:+_3:141260123:+ Neighbours 204 55 0.8325058 0.5428240 Inf 0.8109189
AC079313.1–NCKAP1L 12:54353896:+_12:54499355:+ Neighbours 3 1 0.7484239 0.0815259 Inf 0.8198884
AC010332.1–ZNF880 19:52392788:+_19:52369787:+ Local Rearrangement 3 1 0.7484239 0.0815259 Inf 0.8198884
RNF144A–AC013460.1 2:7030215:+_2:7421184:+ Distant Proximity 3 1 0.7484239 0.0815259 Inf 0.8198884
B3GALT5–AF064860.1 21:39605225:+_21:39725838:+ Overlapping Neighbours 3 1 0.7484239 0.0815259 Inf 0.8198884
SLC38A9–MTREX 5:55697846:-_5:55340010:+ Distant Proximity 3 1 0.7484239 0.0815259 Inf 0.8198884
AC009315.1–FSIP2 2:185483091:+_2:185739346:+ Distant Proximity 154 43 0.8174895 0.5395972 Inf 0.8349925
AC012414.4–AC012414.2 15:20755930:-_15:20759907:- Local Rearrangement 8 3 0.6597751 0.1866294 Inf 0.8413667
MFSD14C–ZNF510 9:96918643:-_9:96776245:- Distant Proximity 8 3 0.6597751 0.1866294 Inf 0.8413667
CHST9–AQP4 18:27024116:-_18:26862596:- Neighbours 5 2 0.6204697 0.1262877 Inf 0.8535156
AC120193.1–AC023202.1 8:24296154:-_8:24183283:- Distant Proximity 5 2 0.6204697 0.1262877 Inf 0.8535156
BNIP3L–DPYSL2 8:26408376:+_8:26581969:+ Neighbours 5 2 0.6204697 0.1262877 Inf 0.8535156
TMED3–MINAR1 15:79314005:+_15:79456098:+ Neighbours 7 3 0.5758904 0.1565446 Inf 0.8815093
LINC00869–SEC22B3P 1:149607554:+_1:148779001:- Distant Proximity 2 1 0.4981146 0.0386191 Inf 0.8966433
CSTF3–FBXO3 11:33141667:-_11:33742084:- Distant Proximity 2 1 0.4981146 0.0386191 Inf 0.8966433
AP002784.1–PANX1 11:94189083:+_11:94178369:+ Local Rearrangement 2 1 0.4981146 0.0386191 Inf 0.8966433
PSPC1–ZMYM5 13:19759323:-_13:19835689:- Local Rearrangement 2 1 0.4981146 0.0386191 Inf 0.8966433
USP22–RN7SL1 17:21000941:-_14:49586613:+ Inter Chromosomal 2 1 0.4981146 0.0386191 Inf 0.8966433
PANTR1–LINC01114 2:104851312:-_2:104749489:- Neighbours 2 1 0.4981146 0.0386191 Inf 0.8966433
MMP24OS–EDEM2 20:35272005:-_20:35142478:- Neighbours 2 1 0.4981146 0.0386191 Inf 0.8966433
AC025465.1–LINC01170 5:124512257:-_5:124386273:- Neighbours 2 1 0.4981146 0.0386191 Inf 0.8966433
ZNRF2P1–FKBP9 7:32729009:+_7:32974617:+ Distant Proximity 2 1 0.4981146 0.0386191 Inf 0.8966433
OR51S1–TP53I11 11:4848669:-_11:44933050:- Distant Proximity 6 3 0.4924414 0.1269719 Inf 0.9164357
KHDRBS2-OT1–KHDRBS2 6:61652255:-_6:61732764:- Overlapping Neighbours 6 3 0.4924414 0.1269719 Inf 0.9164357
LINC01572–PMFBP1 16:72284572:-_16:72174070:- Neighbours 5 3 0.4094664 0.0980454 Inf 0.9453606
PPP4R3B–CCDC88A 2:55558775:-_2:55418916:- Distant Proximity 7 4 0.4273438 0.1283228 Inf 0.9517590
AL050309.1–KLF8 X:56014961:+_X:56250231:+ Neighbours 7 4 0.4273438 0.1283228 Inf 0.9517590
AL391840.3–SH3BGRL2 6:79538843:+_6:79673614:+ Neighbours 272 75 0.6187910 0.3493038 Inf 0.9596768
ST6GALNAC5–AL035409.2 1:76868742:+_1:77068084:+ Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
AC093423.3–ZNF326 1:89843782:+_1:89998110:+ Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
RAB38–AP000676.5 11:88149675:-_11:87954906:- Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
TUBA1B–PTMS 12:49127984:-_12:6770157:+ Distant Proximity 1 1 0.2489532 0.0064235 Inf 0.9603563
TUBA1A–PTMS 12:49127984:-_12:6770157:+ Distant Proximity 1 1 0.2489532 0.0064235 Inf 0.9603563
SMG1–NPIPB13 16:18858170:-_16:30245853:- Distant Proximity 1 1 0.2489532 0.0064235 Inf 0.9603563
LINC01572–PMFBP1 16:72249163:-_16:72171268:- Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
LINC01572–PMFBP1 16:72267552:-_16:72164916:- Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
PDK1–RAPGEF4 2:172670884:+_2:172795025:+ Distant Proximity 1 1 0.2489532 0.0064235 Inf 0.9603563
ABLIM2–AFAP1 4:7983264:-_4:7872080:- Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
KHDRBS2-OT1–KHDRBS2 6:61652255:-_6:61697253:- Overlapping Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
FAM155B–EDA X:69506143:+_X:69957027:+ Neighbours 1 1 0.2489532 0.0064235 Inf 0.9603563
LINC01933–AC008571.2 5:152270360:+_5:152537704:+ Distant Proximity 3 3 0.2447366 0.0435728 Inf 0.9837215
TVP23C–AC005703.3 17:15540433:-_17:15416233:- Neighbours 1 2 0.1233715 0.0042115 Inf 0.9922129 yes
TVP23C-CDRT4–AC005703.3 17:15540433:-_17:15416233:- Neighbours 1 2 0.1233715 0.0042115 Inf 0.9922129 yes
AC074286.1–AC092162.2 2:177094575:-_2:176792644:- Distant Proximity 1 2 0.1233715 0.0042115 Inf 0.9922129
CRYBB2P1–GRK3 22:25459515:+_22:25644592:+ Neighbours 1 2 0.1233715 0.0042115 Inf 0.9922129
LINC01933–AC008571.2 5:152267355:+_5:152375103:+ Distant Proximity 1 2 0.1233715 0.0042115 Inf 0.9922129
MAPT–KANSL1 17:45978440:+_17:46094701:- Local Inversion 2 3 0.1629334 0.0199570 Inf 0.9935909
B3GALT5–AF064860.1 21:39613067:+_21:39725838:+ Overlapping Neighbours 2 3 0.1629334 0.0199570 Inf 0.9935909
EFCAB2–KIF26B 1:245083688:+_1:245366834:+ Neighbours 13 9 0.3382355 0.1478283 Inf 0.9950241
PXDC1–AL033523.1 6:3737079:-_6:3594535:- Neighbours 1 3 0.0813852 0.0031107 Inf 0.9984844
ELAPOR1–ELAPOR2 1:109200237:+_7:86891889:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
RAP1A–RAP1B 1:111691417:+_12:68650400:+ Inter Chromosomal 0 2 0.0000000 0.0000000 Inf 1.0000000
CROCCP2–AL391832.4 1:16625775:-_1:234814281:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
WDTC1–MYG1 1:27303795:+_12:53306680:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
RCC1–STRAP 1:28506084:+_12:15894047:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
SSBP3–SSBP2 1:54239129:-_5:81440636:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
NFIA-AS2–AC099792.1 1:60988645:-_1:60826585:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
AL033530.1–AL691520.1 1:68882003:+_1:69013503:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
CADM1–LRP5 11:115504271:-_11:68347847:+ Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000 yes
ZNF195–RPL13A 11:3370975:-_19:49491425:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
PHF21A–LINC02489 11:46076754:-_11:46256541:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
MALAT1–DAG1 11:65505019:+_3:49530797:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AP003071.5–MYEOV 11:69135532:+_11:69341510:+ Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
CPSF6–TPTEP2-CSNK1E 12:69262562:+_22:38336706:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000 yes
SOCS2–TGFBI 12:93583028:+_5:136063638:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
TMPO–VSIG10 12:98528012:+_12:118073992:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
NAXD–ING1 13:110615647:+_13:110719229:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
TSC22D1–TSC22D2 13:44436044:-_3:150458376:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
EFCAB11–AL137230.1 14:89931541:-_14:89629136:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
AC012405.1–AC073941.1 15:46410353:+_15:46804641:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
AC037433.1–AC009654.1 15:60223070:-_15:60074935:- Neighbours 0 3 0.0000000 0.0000000 Inf 1.0000000
AC138932.3–NOMO1 16:14953015:-_16:14894998:+ Local Inversion 0 1 0.0000000 0.0000000 Inf 1.0000000
HS3ST4–USP6NL 16:25693151:+_10:11518574:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AC009070.1–PRMT2 16:81006734:-_21:46643535:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
SMYD4–NASP 17:1827861:-_1:45584108:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
SUZ12P1–CCDC47 17:30769965:+_17:63766194:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000 yes
MAPT–KANSL1 17:45962470:+_17:46094701:- Local Inversion 0 1 0.0000000 0.0000000 Inf 1.0000000
RPL17-C18orf32–RPL17P12 18:49491405:-_2:146194373:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
PPP4R1–STXBP3 18:9588089:-_1:108782422:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
CNN1–CNN3 19:11549469:+_1:94898083:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AC123912.1–ZNF493 19:21569104:-_19:21405761:+ Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
HECW2–SCAMP2 2:196433132:-_15:74848645:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
ARMC9–LYRM1 2:231240041:+_16:20915556:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
TET3–DGUOK 2:74003166:+_2:73946719:+ Local Rearrangement 0 1 0.0000000 0.0000000 Inf 1.0000000
ANKRD36C–AC008268.1 2:95884173:-_2:95667917:+ Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
SNAP25–SRP72 20:10284772:+_4:56500536:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
EPB41L1–EPB41L2 20:36187763:+_6:130895119:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AL031686.1–ZNF334 20:46474501:-_20:46504740:- Local Rearrangement 0 1 0.0000000 0.0000000 Inf 1.0000000
CRYBB2P1–GRK3 22:25520733:+_22:25661576:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
METTL6–SH3BP5 3:15424955:-_3:15304231:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
GPR149–DHX36 3:154421039:-_3:154316163:- Neighbours 0 2 0.0000000 0.0000000 Inf 1.0000000
CCNL1–SMARCA2 3:157157023:-_9:2181571:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
RPL22L1–RPL22P22 3:170868013:-_X:82506571:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
FGF12–AC092966.1 3:192727181:-_3:193169464:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
ZNF589–FBXW12 3:48260939:+_3:48373308:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000 yes
ERC2–WNT5A 3:55606780:-_3:55480918:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
CAMK2D–PBX3 4:113509638:-_9:125960684:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AC053527.2–ALB 4:73302385:+_4:73404369:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
SEPTIN11–CCNI 4:76949930:+_4:77066405:- Local Inversion 0 1 0.0000000 0.0000000 Inf 1.0000000
LINC02200–APC 5:112632097:+_5:112754873:+ Neighbours 0 2 0.0000000 0.0000000 Inf 1.0000000
CTNNA1–CTNNA2 5:138887642:+_2:80544982:+ Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
AC114316.1–NR2F1-AS1 5:92204684:+_5:93563463:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
AC026780.2–NR2F1-AS1 5:92688120:-_5:93411509:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
SNAP91–PICALM 6:83707798:-_11:86031611:- Inter Chromosomal 0 1 0.0000000 0.0000000 Inf 1.0000000
HOXA1–SKAP2 7:27095261:-_7:26844137:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
AC211476.4–CCDC146 7:73072670:+_7:77236947:+ Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
XKR6–LONRF1 8:10924634:-_8:12743282:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000
CASC9–AC100782.1 8:75324221:-_8:75029459:- Neighbours 0 3 0.0000000 0.0000000 Inf 1.0000000
STK3–VPS13B 8:98749276:-_8:99134632:+ Local Inversion 0 2 0.0000000 0.0000000 Inf 1.0000000
ZNF483–ECPAS 9:111534353:+_9:111444494:- Local Inversion 0 1 0.0000000 0.0000000 Inf 1.0000000 yes
ABHD17B–CEMIP2 9:71862551:-_9:71750385:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
AC073529.1–MID1 X:11055936:-_X:10567603:- Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
CLIC2–AC234781.1 X:155334371:-_X:155335249:- Local Rearrangement 0 1 0.0000000 0.0000000 Inf 1.0000000
AL050309.1–KLF8 X:56014961:+_X:56265180:+ Neighbours 0 1 0.0000000 0.0000000 Inf 1.0000000
NLGN4X–PUDP X:6029280:-_X:6706466:- Distant Proximity 0 1 0.0000000 0.0000000 Inf 1.0000000

Fig S13 Variants & fusion types & genetic groups

Variants

Base substitution proportions

base_substitutions.als_ctrl.sd <- plot_spectrum(type_occurrences, by = answerals.metadata$condition, CT = FALSE, indv_points = TRUE, error_bars = "stdev") # error bars SD rather than 95% CI
base_substitutions.als_ctrl.sd

tb_per_sample <- type_occurrences[, seq_len(6)] %>% tibble::rownames_to_column("sample") %>% 
        dplyr::mutate(condition = factor(toupper(answerals.metadata$condition), levels = c("CTRL","ALS"))) %>% tidyr::pivot_longer(c(-sample, 
        -condition), names_to = "variable", values_to = "nmuts") %>% 
        dplyr::group_by(sample) %>% dplyr::mutate(value = nmuts/sum(nmuts)) %>% 
        dplyr::ungroup() %>% dplyr::mutate(sub_type = stringr::str_remove(variable, 
        " .*"), variable = factor(variable, levels = unique(variable)))
tb <- tb_per_sample %>% dplyr::group_by(condition, variable) %>% dplyr::summarise(sub_type = sub_type[[1]], 
        mean = mean(value), stdev = stats::sd(value), total_individuals = sum(value), 
        total_mutations = sum(nmuts)) %>% dplyr::mutate(total_individuals = sum(total_individuals), 
        total_mutations = sum(total_mutations)) %>% dplyr::mutate(sem = stdev/sqrt(total_individuals), 
        error_95 = ifelse(total_individuals > 1, qt(0.975, df = total_individuals - 
            1) * sem, NA)) %>% dplyr::ungroup() %>% dplyr::mutate(total_mutations = prettyNum(total_mutations, 
        big.mark = ","), total_mutations = paste("No. mutations = ", 
        total_mutations), error_pos = mean)
tb_per_sample = left_join(tb_per_sample, tb[, c("condition", "sub_type", "total_mutations")], by = c("condition", "sub_type"))
base_substitutions.als_ctrl.sd.type <- ggplot(data = tb_per_sample, aes(x = condition, y = value, colour = condition)) + 
    ggrastr::rasterise(geom_violin(adjust = 1), dpi = 72) +
    ggrastr::rasterise(geom_sina(size = 0.5), dpi = 72) +
    ggrastr::rasterise(geom_boxplot(aes(fill = condition), colour = "black", width=0.2, alpha = 0.5, outlier.shape = NA), dpi = 72) + 
    scale_colour_manual(values = c("dodgerblue2", "firebrick2")) + scale_fill_manual(values = c("dodgerblue2", "firebrick2")) +
    theme_bw() + xlab("") + ylab("Relative proportions") + 
    theme_oz() + theme(panel.spacing.x = unit(0.5, "lines"), legend.position = "none") + 
    facet_wrap(~ sub_type, scales = "free", nrow = 2)
base_substitutions.als_ctrl.sd.type

Genetic subgroups

answerals.vcfannotate.mutation = answerals.vcfannotate %>% mutate(genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic",mutation %in% c("ctrl","iso") ~ "CTRL"), genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "C9orf72", "SOD1"))) %>% #mutation == "fus" ~ "FUS","FUS",  mutation == "tardbp" ~ "TARDBP", "TARDBP", 
  drop_na(genetic_group) %>% # remove all other mutants n < 3.
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, total, genetic_group, CONDITION, total_reads, mutation) # keep 1 row per sample

answerals.metadata_genetic_subgroup = answerals.metadata %>% filter(mutation %in%  c("ctrl", "iso", "sporadic", "sod1", "c9orf72")) #"fus", "tardbp", 
answerals.vcfannotate.samples_no_variants = answerals.metadata_genetic_subgroup$dataset_sample[!answerals.metadata_genetic_subgroup$dataset_sample %in% answerals.vcfannotate.mutation$dataset_sample]
answerals.vcfannotate.mutation.totals = answerals.vcfannotate.mutation %>% distinct(dataset_sample, .keep_all = TRUE) #keep 1 row per sample for total number of variants

# generalised linear model spline
## sporadic
answerals.vcfannotate.mutation.totals.glm.sporadic = glm(data=filter(answerals.vcfannotate.mutation.totals, genetic_group %in% c("Sporadic", "CTRL")), total ~ genetic_group + rms::rcs(total_reads, 3), family = poisson)
summary(answerals.vcfannotate.mutation.totals.glm.sporadic)
## 
## Call:
## glm(formula = total ~ genetic_group + rms::rcs(total_reads, 3), 
##     family = poisson, data = filter(answerals.vcfannotate.mutation.totals, 
##         genetic_group %in% c("Sporadic", "CTRL")))
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -20.781   -7.213   -2.644    2.758   48.707  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                           1.064e+01  3.849e-03 2764.35   <2e-16 ***
## genetic_groupSporadic                 1.365e-02  7.146e-04   19.11   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads   4.026e-09  4.936e-11   81.55   <2e-16 ***
## rms::rcs(total_reads, 3)total_reads' -2.007e-09  5.421e-11  -37.02   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 48341  on 241  degrees of freedom
## Residual deviance: 33515  on 238  degrees of freedom
## AIC: 36626
## 
## Number of Fisher Scoring iterations: 3
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           1.064e+01  3.849e-03 2764.35   <2e-16 ***
# genetic_groupSporadic                 1.365e-02  7.146e-04   19.11   <2e-16 ***

# Violin total variant events
answerals.vcfannotate.mutation.stat <- answerals.vcfannotate.mutation %>% wilcox_test(total ~ genetic_group) %>% add_significance() %>% add_xy_position() %>% filter(group1 == "CTRL") %>%
  mutate(p.adj.signif = case_when(group2 == "Sporadic" ~ "****", TRUE ~ p.adj.signif), y.position = case_when(group2 == "Sporadic" ~ 75000, TRUE ~ y.position))
answerals.vcfannotate.mutation.violin <- violin_plot(answerals.vcfannotate.mutation.totals, color_by = "genetic_group", continuous = "total", cols = c("dodgerblue2","firebrick2","forestgreen","gold2","purple","grey"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(50000,76000), dpi = 72, ylabel = "Number of Variants") +
  stat_pvalue_manual(answerals.vcfannotate.mutation.stat, tip.length = 0.01, size = 4, hide.ns = TRUE)
answerals.vcfannotate.mutation.violin

Fusions

Fusion types

ipsc_mn_als_datasets.starfusion.fusion_type_n = ipsc_mn_als_datasets.starfusion %>% 
  add_count(dataset_sample, fusion_type) %>% # count number of fusion types per sample
  distinct(dataset_sample, fusion_type, .keep_all = TRUE) %>% select(dataset_sample, fusion_type, n, condition, dataset, total_reads) #keep 1 row per sample fusion type
# add samples with 0 fusions for each fusion type
samples_no_neighbours = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Neighbours"),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_neighbours = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_neighbours) %>% mutate(fusion_type = "Neighbours", n = 0) %>% 
  select(dataset_sample, n, condition, fusion_type)
samples_no_local_rearrangement = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Local\nRearrangement"),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_local_rearrangement = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_local_rearrangement) %>% mutate(fusion_type = "Local\nRearrangement", n = 0) %>%
  select(dataset_sample, n, condition, fusion_type)
samples_no_local_inversion = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Local\nInversion"),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_local_inversion = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_local_inversion) %>% mutate(fusion_type = "Local\nInversion", n = 0) %>% 
  select(dataset_sample, n, condition, fusion_type)
samples_no_overlapping_neighbours = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Overlapping\nNeighbours"),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_overlapping_neighbours = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_overlapping_neighbours) %>% mutate(fusion_type = "Overlapping\nNeighbours", n = 0) %>% 
  select(dataset_sample, n, condition, fusion_type)
samples_no_distant_proximity = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Distant\nProximity" ),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_distant_proximity = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_distant_proximity) %>% mutate(fusion_type = "Distant\nProximity" , n = 0) %>% 
  select(dataset_sample, n, condition, fusion_type)
samples_no_inter_chromosomal = ipsc_mn_als_datasets.paired_end.metadata$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata$dataset_sample %in% pull(filter(ipsc_mn_als_datasets.starfusion.fusion_type_n,fusion_type == "Inter\nChromosomal"),dataset_sample)]
ipsc_mn_als_datasets.paired_end.metadata.no_inter_chromosomal = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset_sample %in% samples_no_inter_chromosomal) %>% mutate(fusion_type = "Inter\nChromosomal", n = 0) %>% 
  select(dataset_sample, n, condition, fusion_type)
ipsc_mn_als_datasets.starfusion.fusion_type_n = bind_rows(ipsc_mn_als_datasets.starfusion.fusion_type_n, ipsc_mn_als_datasets.paired_end.metadata.no_neighbours, ipsc_mn_als_datasets.paired_end.metadata.no_local_rearrangement, ipsc_mn_als_datasets.paired_end.metadata.no_local_inversion, 
                                                          ipsc_mn_als_datasets.paired_end.metadata.no_overlapping_neighbours, ipsc_mn_als_datasets.paired_end.metadata.no_distant_proximity, ipsc_mn_als_datasets.paired_end.metadata.no_inter_chromosomal) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), 
         fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")))

### Inter_Chromosomal
glm_starfusion_Inter_Chromosomal = glm(data = filter(ipsc_mn_als_datasets.starfusion.fusion_type_n, fusion_type == "Inter\nChromosomal"), n ~ CONDITION + dataset + rms::rcs(total_reads, 3), family=poisson)
summary(glm_starfusion_Inter_Chromosomal)
## 
## Call:
## glm(formula = n ~ CONDITION + dataset + rms::rcs(total_reads, 
##     3), family = poisson, data = filter(ipsc_mn_als_datasets.starfusion.fusion_type_n, 
##     fusion_type == "Inter\nChromosomal"))
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.5908  -0.3609  -0.2594   0.3255   1.6615  
## 
## Coefficients:
##                                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                          -1.547e-01  1.269e+00  -0.122 0.902967    
## CONDITIONALS                          6.354e-01  1.717e-01   3.700 0.000216 ***
## datasetcatanese                      -1.414e-01  4.205e-01  -0.336 0.736669    
## datasetdafinca.c9orf72                1.712e-01  1.099e+00   0.156 0.876214    
## datasetdafinca.tardbp                 1.176e-01  9.441e-01   0.125 0.900858    
## datasetdesantis                       2.212e-01  8.711e-01   0.254 0.799528    
## datasetkiskinis                       2.404e+00  1.037e+00   2.317 0.020488 *  
## datasetneurolincs.diMN               -3.735e-02  3.225e-01  -0.116 0.907791    
## datasetneurolincs.iMN                -4.341e-01  7.340e-01  -0.591 0.554279    
## datasetwang                           1.406e+00  7.545e-01   1.863 0.062466 .  
## rms::rcs(total_reads, 3)total_reads  -3.379e-10  2.106e-08  -0.016 0.987194    
## rms::rcs(total_reads, 3)total_reads' -3.008e-09  1.343e-08  -0.224 0.822832    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 229.815  on 131  degrees of freedom
## Residual deviance:  37.707  on 120  degrees of freedom
##   (264 observations deleted due to missingness)
## AIC: 363.08
## 
## Number of Fisher Scoring iterations: 4
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                          -1.546e-01  1.269e+00  -0.122 0.903002    
# CONDITIONALS                          6.354e-01  1.717e-01   3.700 0.000216 ***

ipsc_mn_als_datasets.starfusion.fusion_type.stat <- ipsc_mn_als_datasets.starfusion.fusion_type_n %>% group_by(fusion_type) %>% t_test(n ~ CONDITION) %>% mutate(p.signif = c("ns","ns","ns","ns","ns","***"), y.position = 24) 

ipsc_mn_als_datasets.starfusion.fusion_type.violin <- ggplot(ipsc_mn_als_datasets.starfusion.fusion_type_n, aes(x = CONDITION, y = n, colour = CONDITION)) +
    # ggrastr::rasterise(geom_violin(adjust = 2), dpi = 72) +
    ggrastr::rasterise(geom_sina(size = 0.5), dpi = 72) +
    ggrastr::rasterise(geom_boxplot(aes(fill = CONDITION), colour = "black", width=0.2, alpha = 0.5, outlier.shape = NA), dpi = 72) + 
    scale_colour_manual(values = c("dodgerblue2", "firebrick2")) + scale_fill_manual(values = c("dodgerblue2", "firebrick2")) +
    theme_oz() + theme(legend.position = "none", plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5), panel.border = element_blank(), axis.ticks = element_line(colour = "black") ) +
    facet_wrap(~ fusion_type, scales = "free", nrow = 2)  + labs(y = "Number of Fusion Events", x = "") +
    stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.fusion_type.stat, label = "p.signif", tip.length = 0.01, size = 4, hide.ns = TRUE) 
ipsc_mn_als_datasets.starfusion.fusion_type.violin

# histogram
ipsc_mn_als_datasets.starfusion.fusion_type.histogram = ggplot(ipsc_mn_als_datasets.starfusion.fusion_type_n, aes(x=n, color=CONDITION, fill=CONDITION)) +
  geom_histogram(alpha=0.5, position="identity", binwidth = 1)+
  scale_color_manual(values=c("dodgerblue2", "firebrick2"))+ scale_fill_manual(values=c("dodgerblue2", "firebrick2"))+
  facet_wrap(~ fusion_type, scales = "free", nrow = 2) + theme_oz() #+ ggtitle("Zeros filled")
ipsc_mn_als_datasets.starfusion.fusion_type.histogram

Genetic subgroups

# Sporadic
ipsc_mn_als_datasets.starfusion.sporadic = read_csv(here(proj_path,"rnafusion/ipsc_mn_als_datasets.starfusion.csv")) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")),
         genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>%
  filter(dataset %in% c("answerals","neurolincs.diMN"), mutation %in% c("ctrl","iso","sporadic")) %>% left_join(multiqc_rseqc_read_distribution.tsv)

ipsc_mn_als_datasets.starfusion.sporadic.n = ipsc_mn_als_datasets.starfusion.sporadic %>% 
  add_count(dataset_sample) %>% # count number of fusion per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, genetic_group, mutation, dataset, total_reads) #keep 1 row per sample
ipsc_mn_als_datasets.starfusion.sporadic.n.stats = tibble(group1 = "CTRL", group2 = "Sporadic", p.signif = "ns", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.sporadic.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.sporadic.n, color_by = "genetic_group", continuous = "n", cols = c("dodgerblue2", "firebrick2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,43), dpi = 72, ylabel = "Number of Fusion Events") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.sporadic.n.stats, tip.length = 0.01, size = 4, hide.ns = TRUE)

# C9orf72
ipsc_mn_als_datasets.starfusion.c9orf72 = read_csv(here(proj_path,"rnafusion/ipsc_mn_als_datasets.starfusion.csv")) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")),
         genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>%
  filter(dataset %in% c("answerals","neurolincs.diMN","catanese","dafinca.c9orf72","neurolincs.iMN","sommer"), mutation %in% c("ctrl","iso","c9orf72")) %>% left_join(multiqc_rseqc_read_distribution.tsv)
ipsc_mn_als_datasets.starfusion.c9orf72.n = ipsc_mn_als_datasets.starfusion.c9orf72 %>% 
  add_count(dataset_sample) %>% # count number of fusion per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, genetic_group,  mutation, dataset, total_reads) #keep 1 row per sample
 # add samples with 0 fusions

# glm_starfusion.c9orf72 = glm(data = ipsc_mn_als_datasets.starfusion.c9orf72.n, n ~ genetic_group + dataset + rms::rcs(total_reads, 3), family=poisson)
# summary(glm_starfusion.c9orf72)
# Coefficients:
#                                        Estimate Std. Error z value Pr(>|z|)    
# (Intercept)                           2.783e+00  5.216e-01   5.336 9.50e-08 ***
# CONDITIONALS                          2.401e-01  6.037e-02   3.978 6.96e-05 ***

# Violin
ipsc_mn_als_datasets.starfusion.c9orf72.n.stats = tibble(group1 = "CTRL", group2 = "C9orf72", p.signif = "****", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.c9orf72.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.c9orf72.n, color_by = "genetic_group", continuous = "n", cols = c("dodgerblue2", "forestgreen"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,43), dpi = 72, ylabel = "Number of Unique Fusion Events") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.c9orf72.n.stats, tip.length = 0.01, size = 4, hide.ns = TRUE)


# TARDBP
ipsc_mn_als_datasets.starfusion.tardbp = read_csv(here(proj_path,"rnafusion/ipsc_mn_als_datasets.starfusion.csv")) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")),
         genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>%
  filter(dataset %in% c("answerals","dafinca.tardbp","smith"), mutation %in% c("ctrl","iso","tardbp")) %>% left_join(multiqc_rseqc_read_distribution.tsv)
ipsc_mn_als_datasets.starfusion.tardbp.n = ipsc_mn_als_datasets.starfusion.tardbp %>% 
  add_count(dataset_sample) %>% # count number of fusion per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, genetic_group, mutation, dataset, total_reads) #keep 1 row per sample
 # add samples with 0 fusions
ipsc_mn_als_datasets.paired_end.metadata.tardbp = ipsc_mn_als_datasets.paired_end.metadata %>% filter(dataset %in% c("answerals","dafinca.tardbp","smith"), mutation %in% c("ctrl","iso","tardbp"))
ipsc_mn_als_datasets.starfusion.samples_no_fusions.tardbp = ipsc_mn_als_datasets.paired_end.metadata.tardbp$dataset_sample[!ipsc_mn_als_datasets.paired_end.metadata.tardbp$dataset_sample %in% ipsc_mn_als_datasets.starfusion.tardbp.n$dataset_sample] 
ipsc_mn_als_datasets.paired_end.metadata.no_fusions.tardbp = ipsc_mn_als_datasets.paired_end.metadata.tardbp %>% filter(dataset_sample %in% ipsc_mn_als_datasets.starfusion.samples_no_fusions.tardbp) %>% 
  left_join(multiqc_rseqc_read_distribution.tsv) %>%
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), n = 0, genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>% select(dataset_sample, n, CONDITION, mutation, dataset, total_reads, genetic_group)
ipsc_mn_als_datasets.starfusion.tardbp.n = bind_rows(ipsc_mn_als_datasets.starfusion.tardbp.n, ipsc_mn_als_datasets.paired_end.metadata.no_fusions.tardbp)

# Violin
ipsc_mn_als_datasets.starfusion.tardbp.n.stats = tibble(group1 = "CTRL", group2 = "TARDBP", p.signif = "ns", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.tardbp.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.tardbp.n, color_by = "genetic_group", continuous = "n", cols = c("dodgerblue2", "purple"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,43), dpi = 72, ylabel = "Number of Fusion Events") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.tardbp.n.stats, tip.length = 0.01, size = 4, hide.ns = TRUE)

# FUS
ipsc_mn_als_datasets.starfusion.fus = read_csv(here(proj_path,"rnafusion/ipsc_mn_als_datasets.starfusion.csv")) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")),
         genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>%
  filter(dataset %in% c("catanese","desantis"), mutation %in% c("ctrl","iso","fus")) %>% left_join(multiqc_rseqc_read_distribution.tsv)
ipsc_mn_als_datasets.starfusion.fus.n = ipsc_mn_als_datasets.starfusion.fus %>% 
  add_count(dataset_sample) %>% # count number of fusion per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, genetic_group, mutation, dataset, total_reads) #keep 1 row per sample
 # add samples with 0 fusions

# Violin
ipsc_mn_als_datasets.starfusion.fus.n.stats = tibble(group1 = "CTRL", group2 = "FUS", p.signif = "ns", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.fus.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.fus.n, color_by = "genetic_group", continuous = "n", cols = c("dodgerblue2", "grey"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,43), dpi = 72, ylabel = "Number of Fusion Events") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.fus.n.stats, tip.length = 0.01, size = 4, hide.ns = TRUE)

# SOD1
ipsc_mn_als_datasets.starfusion.sod1 = read_csv(here(proj_path,"rnafusion/ipsc_mn_als_datasets.starfusion.csv")) %>% 
  mutate(CONDITION = factor(toupper(condition), levels = c("CTRL","ALS")), fusion_type = factor(fusion_type, levels = c("Local\nInversion", "Local\nRearrangement", "Neighbours", "Overlapping\nNeighbours", "Distant\nProximity", "Inter\nChromosomal")),
         genetic_group = case_when(mutation == "c9orf72" ~ "C9orf72", mutation == "sod1" ~ "SOD1", mutation == "sporadic" ~ "Sporadic", mutation == "fus" ~ "FUS", mutation == "tardbp" ~ "TARDBP", mutation %in% c("ctrl","iso") ~ "CTRL"), 
         genetic_group = factor(genetic_group, levels = c("CTRL", "Sporadic", "SOD1", "C9orf72", "FUS", "TARDBP"))) %>%
  filter(dataset %in% c("answerals","neurolincs.diMN", "kiskinis","wang"), mutation %in% c("ctrl","iso","sod1")) %>% left_join(multiqc_rseqc_read_distribution.tsv)
ipsc_mn_als_datasets.starfusion.sod1.n = ipsc_mn_als_datasets.starfusion.sod1 %>% 
  add_count(dataset_sample) %>% # count number of fusion per sample
  distinct(dataset_sample, .keep_all = TRUE) %>% select(dataset_sample, n, CONDITION, genetic_group, mutation, dataset, total_reads) #keep 1 row per sample
 # add samples with 0 fusions

# Violin
ipsc_mn_als_datasets.starfusion.sod1.n.stats = tibble(group1 = "CTRL", group2 = "SOD1", p.signif = "****", y.position = 40, xmin = 1, xmax = 2)
ipsc_mn_als_datasets.starfusion.sod1.violin <- violin_plot(ipsc_mn_als_datasets.starfusion.sod1.n, color_by = "genetic_group", continuous = "n", cols = c("dodgerblue2", "gold2"), plot_stats = FALSE, arrow_labels = FALSE, ylims = c(0,43), dpi = 72, ylabel = "Number of Fusion Events") +
  stat_pvalue_manual(ipsc_mn_als_datasets.starfusion.sod1.n.stats, tip.length = 0.01, size = 4, hide.ns = TRUE)

plot_grid(ipsc_mn_als_datasets.starfusion.sporadic.violin, ipsc_mn_als_datasets.starfusion.c9orf72.violin, ipsc_mn_als_datasets.starfusion.sod1.violin, ipsc_mn_als_datasets.starfusion.tardbp.violin, ipsc_mn_als_datasets.starfusion.fus.violin, nrow = 2)